Top Banner

of 400

Business_Statistics_Project2_2010

Apr 08, 2018

Download

Documents

Ankit Mittal
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
  • 8/7/2019 Business_Statistics_Project2_2010

    1/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    1

    Comparative Analysis of Automobile Sector and Telecom Sector

    using ANOVA

    Group:

    NAME Roll No E-Mail ID

    Ankit Mittal 10FN-015 [email protected]

    Anant Shree Goyal 10HR-005 [email protected]

    Ankit Jain 10DM-016 [email protected]

    Abhinav Sharma 10IT-001 [email protected]

  • 8/7/2019 Business_Statistics_Project2_2010

    2/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    2

    1. Summary

    Topic

    Comparative analysis of Automobile sector and Telecom sector using ANOVA.

    Objective

    First, our objective is to determine statistical significance of the data for the individual

    companies and the various statistical parameters for the collected data.

    We want to compare the difference in population means among the different companies of

    Automobile and Telecom sector using one way ANOVA on the basis of closing price. And then

    compare the performance of Automobile sector against Telecom sector using one way ANOVA

    on the basis of closing price for past few years.

    Methodology

    We have used MS-Excel for ANOVA (Analysis of Variance). For ANOVA, we have considered

    data from 31stDec 2008 to 16th Aug 2010.

    Result

    There is a significant Difference in the Population Mean of Automobile and Telecom Sector on

    the basis of Closing Stock Prices (31-12-2008 to 18-08-2010) as obtained through ANOVA.

    2. Introduction

    Our objective is to analyze and do comparative study of stock market data of Automobile sector

    and Telecom sector. For this task, we have identified 5 companies from both the sectors.

    For Automobile Sector we are considering

    yBajaj,

    yHero Honda,

    yHonda Siel,

    yMaruti Suzuki

  • 8/7/2019 Business_Statistics_Project2_2010

    3/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    3

    yTata Motors.

    For Telecom Sector we are taking data of

    y

    Airtel,yIdea Cellular,

    yMTNL,

    yReliance communication

    yTata Telecommunications.

    The tools used for the analysis is

    yMicorsoft Excel 2007

    The technique used for analysis is ANOVA, for which we are considering data from 31stDec2008 till 16

    thAug 2010.

    Telecom Sector

    Studies have shown that in India, the telecom sector has been a major enabler of economic

    growth. An Indian Council forResearch on International Economic Relations (ICRIER) studyhas shown that states with higher mobile penetration are forecast to grow faster. At present, the

    Indian telecom market is the fastest growing in the world with the lowest tariffs and currently

    market leaders in the Indian telecom sector are launching plans to compete with new operators.The year 2009 saw telecom players shift from per minute billing to per second billing.

    Historically, the telecom network in India was owned and managed by the Government

    considering it to be a natural monopoly and strategic service, best under state's control. However,

    in 1990's, examples of telecom revolution in many other countries, which resulted in betterquality of service and lower tariffs, led Indian policy makers to initiate a change process finally

    resulting in opening up of telecom services sector for the private sector.

    Policy reforms can be broadly classified in three distinct phases

    y "The Decade of1980's saw private sector being allowed in telecommunicationsequipment manufacturing. Mahanagar Telephone Nigam Limited (MTNL) and VideshSanchar Nigam Limited (VSNL) were formed and a Telecom Commission was set up to

    give focus to telecommunications policy formation.y "In 1990s, telecommunications sector also benefited from the general opening up of the

    economy. NTP 1994 was the first attempt to give a comprehensive roadmap for theIndian telecommunications sector.

    o Availability of telephones on demand (targeted by 1997)

  • 8/7/2019 Business_Statistics_Project2_2010

    4/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    4

    o Universal service covering all villages and one PCO per500 persons in urban

    areas at the earliest (targeted to be achieved by 1997)o Telecom services at affordable and reasonable prices

    o World standard quality of servicesy

    "

    NTP 1999 brought in the third generations of reforms in the Indian telecommunicationssector.1

    Automobile Sector

    The automotive sector is one of the prime drivers ofIndian economy. Economic liberalization

    policies adopted by government ofIndia have primarily propelled India into the big league, with

    many global automotive players seeking to establish their operations in India. In fact in the last

    five years, India has turned into a big trade mart for the automobile industry, registering a growthrate of15-27 percent.

    Following India's growing openness, the arrival of new and existing models, easy availability offinance at relatively low rate of interest and price discounts offered by the dealers and

    manufacturers all have stirred the demand for vehicles and a strong growth of theIndian automobile industry.

    The data obtained from ministry of commerce and industry, shows high growth obtained since

    2001- 02 in automobile production continuing in the first three quarters of the 2004-05. Annualgrowth was 16.0 per cent in April-December, 2004; the growth rate in 2003-04 was 15.1 per

    cent. The automobile industry grew at a compound annual growth rate (CAGR) of 22 per centbetween 1992 and 1997.

    With investment exceeding Rs. 50,000 crore, the turnover of the automobile industry exceededRs. 59,518 crore in 2002-03. Including turnover of the auto-component sector,

    the automotive industry's turnover, which was above Rs. 84,000 crore in 2002-03, is estimated tohave exceeded Rs.1,00,000 crore ( USD 22. 74 billion) in 2003-04.

    2

    We have used MS-Excel and SPSS tool for ANOVA (Analysis of Variance). For ANOVA, we

    have considered data from 31stDec 2008 to 16th Aug 2010.

  • 8/7/2019 Business_Statistics_Project2_2010

    5/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    5

    3. Literature Review

    Indias Long March to a Global Auto Major:

    A Study of Government Influence on Industry Development in the Post-Independence Era

    By Rajnish Tiwari,Mahipat Ranawat & Andreas Lange

    Institute of Technology & InnovationManagement, TUHH

    Hamburg,March 2010

    www.global-innovation.net

    Objectives ofthe Study:

    1.To IDENTIFY GOVERNMENT POLICIES thathaveinfluencedthedevelopment of Indiasautomotive

    industry

    2.To UNDERSTAND THE INFLUENCE ofgovernmentpolicies onthedevelopment of Indiasautomotive

    industry

    3.To EXPLORE ROLEplayedbythegovernmentinthedevelopment of Indiasautomotiveindustry

    Summary of Govt. Influence on Industry Development

    y Governmentpolicieshave significantlyinfluencedthedevelopment of Indiasautomotive

    industry

    y Some oftheimportantpolicieshavebeenthe onesrelatedto theprotection,indigenisation,

    modernizationand liberalization oftheindustry

    y Therole of Indiangovernmenttransitioned fromregulatoryto facilitative oneastheindustry

    progressedthroughsuccessivestages ofcompetitivedevelopment. Thiswasinalignmentto the

    theoretical framework,butwithsomedeviations

    y However,thetransitionsweremainlybroughtaboutbychanceevents like Oil Crisis, Gulf War,

    etc. Thegovernmenthasto beat leastcredited forimplementation

    y Governmentpoliciesshall continueto playanimportantroleinthe futuredevelopment ofthe

    industrywiththeireffect ondemandand factorconditions

  • 8/7/2019 Business_Statistics_Project2_2010

    6/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    6

    Outlook on Government Policies

    y Therole ofgovernmentwill continueto bethat ofa facilitator facilitate firmsto innovateand

    upgradebymeans ofindustry-specificprogrammes

    y The futuregovernmentpolicieswill affectthedevelopment of Indiasautomotiveindustrylargelythroughtheireffect ondemandandadvanced factorconditions

    y Accordinglythepolicieswill focus ontaxincidences,exports,industry R&D,safety &

    environmental standards,infrastructure,specialisedmanpower,etc.

    y Indianautomotiveindustrywill thriveto attainits owncompetitiveposition (probablysmall

    cars)intheglobal auto industrymovingaway frommerecostadvantages

    COMPETITIVENESSOFFIRMS IN INDIAN AUTOMOBILE INDUSTRY

    February 2009

    BY L. G.Burange & Shruti Yamini

    University OfMumbai

    Department ofEconomics

    www.mu.ac.in/arts/social_science/eco/pdfs/depart/dwp3.pdf

    The efforts have been made to build up an index that reflects thecompetitiveness of firmsinthe

    Indianautomobileindustry. Intheprocessanattempthas also been made to study the current

    status and evolution ofthe industry. Acomposite competitiveness index is defined as the

    mathematical combination ofindividual indicators that represent different dimensions ofthe

    concept whosedescriptionisthe objective oftheanalysis.

    The finding ofthe study reflects the relative competitive position ofthesample firms and also

    the overall picture ofthe industry. Out of fourteen sample firms, performance ofseven firms

    was above the industry average.Maruti Udyog Limitedscoredhighestinthegroupgettingtopmost

    rankingmainlybecause ofnon-financial indicatorssuchasproductiveperformance,customer

    satisfactionetc. Thisis followed by Bajaj Auto, which has scored second rank due to better

    financial performanceinterms ofstockmarketperformance, financial ratiosand foreigntrade. Looking

    atthe financial andnon-financial indexseparately,itisseenthattherankingsdifferslightlyassome

    firmsperformbetterin onethanthe other.

    It is also observed that out of first seven firms, only two are from three-wheeler segment. This

    shows that competition is more intense in the passenger vehicle and two-wheeler segments. The

    commercial vehicle segment seems to bedominatedby TataMotors.

  • 8/7/2019 Business_Statistics_Project2_2010

    7/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    7

    Itcanbehopedthatthe overall index,sub-indicatorindexand financial/ non-financial indexproveto be

    helpful in framingcompetitivepoliciesbythe firms. Itwill also beuseful to consumersto judgethe

    competitiveperformance ofthese firms fromtheproduct qualityandinvestmentpoint of view.

    THE INDIAN AUTOMOTIVE MARKET

    http://www.trade.gov/static/India%20White%20Paper.pdf

    December 2009

    Giventhe largepopulationandgrowingmiddleclass, Indiahasthepotential to developinto asignificant

    market forautomobilemanufacturers. Witha large,Englishspeaking,relatively low-cost laborpool,

    Indiacouldeventuallyserveasamajorregional exporthubthroughoutAsia,Africa,andEurope.

    Mahindra & Mahindra,in fact,isalreadydevelopingplansto beginsellingautomobilesinthe United

    States. Itplansto shipcompletelyknocked-down (CKD)kitsto the United Statesto beassembledin

    Ohio. These CKD kitswouldbeexported from Indiaandshippedto the United States for final assembly.

    TheseplanswouldmakeMahindra & Mahindrathe first Indiancarmanufacturerto setupa

    manufacturing facilityinthe United States. However,thereareanumber of factorsthatmustbe

    overcomein order for India,alongwithautomobilemanufacturers,to fullyrealizethepotential inthe

    Indianmarket. Inparticular, logistical transportationinfrastructurecapabilitieswill needto beimproved

    to meetdomesticandexportneeds. Basedsimply ontheamount ofinvestmentsby GMand Fordalone,

    itisclearthat foreign vehiclemanufacturers view Indiaasacrucial playerinthe future ofthe

    automotiveindustryasaregional exporthub,andasasupplier ofautomobilesandautomotiveparts

    globally.

    The Chinese and Indian Automobile Industry in Perspective : Technology Appropriation, Catching-up

    and Development

    By Xavier Richet, Jean Monnet Chair, Universit Sorbonne nouvelle, Paris

    Joel Ruet, CNRS-LATTS & Visiting Fellow Asia Research Centre, LSE

    http://gdrdeveloppementtransition.org/colloque_2008/RICHET-RUET.pdf

    February 2010

    Thecomparison oftheautomobileindustryin Chinaand Indiaallowsshedding light ontheeconomic

    processes ofemergenceat large. Thereisastarkcontrastinthecapacities ofautonomisationand

    endogenisation ofthesector in the two countries. Thiscontrastservesasananalyser ofthe

    relationshipsbetweenthemodes ofsector openingandthepaths oftechnological catching-upthatisat

    thecore ofthephenomenon ofemergence.

  • 8/7/2019 Business_Statistics_Project2_2010

    8/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    8

    Today Chinaand Indiacarindustryareatthecross-road. Theyhavetransformedthecarindustryboth

    withsimilaranddifferenttoolsandare facingtheworldcompetition. Constrainedbystateregulation,

    theyhaveexperienced openingstrategies,early 80s in China,early 90sin India. China has supported

    the development ofthis sector through bureaucraticmeans andmarketmechanisms: bureaucratic

    as the State and Province has kept a direct control over this industry, Provinces taking advantage

    ofde facto decentralisation to develop locally. As the result, the sector, up to recently was weak

    and fragmented with theexistence ofmorethan 120 carmaker overthecountry. The national

    system ofinnovation in China is weaker than in India. It is throughsuccessivenational industrial

    policyprogrammes that thegovernmentassupported theenhancing ofthissector,promoting

    industrial collaborationswith foreigncarmakers.

    There isadifference in theaimsamongdomesticand foreignpartners. Foreign OEMs are looking for

    profitability, market shares on an expanding market with a stronggrowthpotential. Few ofthem

    are lookingat takingadvantage of lowcosts to exporttoward Western markets. There is a

    different approach concerning suppliers, both foreign and domesticwhich are looking only looking at the domesticmarket but arewillingto takeadvantage ofthe lowcostadvantage for lowtechnology

    products. Foreignmakers face,atthisstage oftheirdevelopment,the followingproblems:

    - property rights issues linked to imitation and fakes (see the Geely-GM row, other Westerncar

    makerhave faced the sameproblem), trust in local arbitrationcourtsandwillingnessto keepthe

    coretechnology.

    -pricewar:competitivewar on lowsegments ofproduction onwhichmarginsare lowcoming fromthe

    newcompetitiveprivatesector.

    - state regulation and state macro-policies in order to curb disequilibrium from anheatingeconomy,to control the financial andbankingsystem.

    -thedifficultyin organizingthesub-contracting sector,up-gradingit.

    Managing Socio-technical Change in Indian Automobile Industry A Survey

    *Dr. Rajiv Kumar Garg

    Proceedings of the World Congress on Engineering, London, U.K. 2009

    http://www.iaeng.org/publication/WCE2009/WCE2009_pp1147-1152.pdf

    Management ofchangehasassumedagreatdeal ofimportancein Indianautomobileindustry.

    Managingchangeisposingabigchallengeto Indian firmsinthewake ofglobalizationand liberalization.

    Successful changedemandsthatall majorareas ofan organizationarekeptin focusconcurrently. These

  • 8/7/2019 Business_Statistics_Project2_2010

    9/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    9

    areasaretechnology,structure,systems,peopleandculture. Itisseenthatall theseareasare

    interwovenandcannotbeemphasizeduponinisolation. Thispaperpresentsthecurrentstatus ofsocio-

    technical changein Indianautomobileindustry. Thestudyhasbeenmadethroughsurveyin Indian

    automobilecompaniesusingaspeciallydesigned questionnaire.

    Conclusion

    Fromthesurvey,itisclearthat Indianautomobilehasmadeeffortsto managesocio-technical change.

    Changeshavebeenmadein variousareas ofchangemanagement liketechnology,systems,structure,

    peopleandculture.Asaresult, variousnotablechangeshavebeenmadein various organizations.But

    still thereiswidescope for furtherchange. Theindustryhasto strivehardto beinnovative,

    technologicallysuperioraswell asworking-cultureconscious. Thecontinuouspacewithworld-class

    technology,supportivesystems,restructuringandcultural modificationswill helpthe organizationsto

    changesuccessfully.

    An Overview of the Indian Telecommunications Industry

    Gaurav Dixit -Manager www.careratings.com

    May 28, 2010

    http://www.careratings.com/current/3/7683.pdf

    Introduction

    Drivenby variouspolicy initiatives, the Indian telecomsectorwitnessed a complete transformation

    in the last decade. The Indian telecom industryhasproved to be the fastestgrowingin theworld

    and is currently the second largest globally bysubscriberbase. The success ofthe sector can be

    attributed largely to the growth in the wireless segment,with the operators reporting additions

    ofapproximately 10-15 millionsubscribers every month. The telecom markets in the Asia Pacific

    region are expected to experience the highest growthrate (nearly 16 percent)inthenext fiveyears

    ledby Indiaand China. The total number ofsubscribers in India increased to 621.28 million in

    March 2010 from 600.98 million in February 2010 thereby registering a growth of 3.38%. With this

    the overall teledensity in India reached 52.74%. Over the period 1998-2009 thenumber oftelecom

    subscribersin Indiagrewata CAGR of 33.44%.

    Conclusion

  • 8/7/2019 Business_Statistics_Project2_2010

    10/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    10

    Theyear 2009 wasa landmark one forthe Indiantelecommunicationsindustrymarkedbyatremendous

    growthinsubscriberbasewhich leadto Indiabeatingthe US to becomethesecond largesttelecom

    marketglobally. However,to sustainthegrowthmomentuminthecomingyearsandto addnew

    dimensionsto it,anumber ofreformsandinitiativesmustbe undertaken. The Government needs to

    revise its M&A policies to facilitateconsolidationinthe overcrowdedtelecommarketto ensurethat

    itcontinuesto grow,notjustinsubscriberbasebutinterms ofrevenuesaswell. Policiesalso needto be

    developed forsharing ofspectrumso asto providereliefto the operatorswhosecapital structuresare

    already strained owing to thedebt raised for 3G auctions.Although voice serviceshavebeenthekey

    contributorsto thegrowth ofthetelecomsector,withthe oncoming 3G roll outthesectorispoised for

    ashiftin focus from voiceto valueaddedservicesinabigway. With the saturation in theurban

    markets, thenextarea of focus for the operators is therural and semi urban areas that are still

    largely untapped and provide a tremendouspotential for growth. These new avenues for growth

    combined with the proactivemeasuresinitiatedbythe Governmentare likelyto heraldthenextphase

    ofdevelopment forthe Indiantelecommunicationssector.

    Trends Of Indian Telecom Industry

    Mercurius Advisory Services Private Limited (MAS) and AJSH & Co, Chartered Accountants (AJSH)

    June 2010

    http://gaj-india.com/usefulupdates/indiantelecom%20june%202010.pdf

    Important Facts & Conclusions

    1. Thenumber oftelephonesubscribers in India increased from 509.03 Millionattheend of Sep-09 to

    562.16 Millionatthe end of Dec-09, registering a growth of 10.4%. The overall Teledensity in

    India has reached 47.88 as on 31st December 2009.

    2. Subscription in UrbanAreas grew from 357.22 Million at theend of Sep-09 to 387.63 Million at

    the end of Dec-09,takingtheurban Teledensity from 102.79 to 110.96. Rural subscriptionincreased

    from 151.81 Millionto 174.53 Million leadingto increasein Rural Teledensity from 18.46 to 21.16,duringthisperiod.

    3. About 57% ofthe total netadditionshavebeen inurbanareasas compared to 65% in the

    previous quarter. This in otherwords,impliesrapidincreaseinrural subscriptionsduringthe quarter.

    However,thisuptakeinrural subscriptionisinwirelesssegment. Theshare ofrural subscribershas

    increasedto 31%intotal subscription from 29.8%in Sep-09.

  • 8/7/2019 Business_Statistics_Project2_2010

    11/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    11

    4. With 53.37 Millionnetadditionsduringthe Quarter, Total Wireless (GSM + CDMA)subscriberbase

    increasedto 525.09 Millionattheend of Dec-09,andwireless Tele-densityreached 44.72.

    5. Wire linesubscriberbasedeclined from 37.31 millionin Sep-09 to 37.06 Millionattheend of Dec-09,

    bringingdownthewire lineteledensityto 3.16 from 3.19 in Sep-09

    6. Internetsubscribersincreased from 14.63 millionto 15.24 millionattheend of December 2009

    registeringa quarterlygrowthrate of 4.21%. Top 10 ISPstogetherhold 95.93% ofthetotal Internet

    subscriberbase.

    7. Share ofBroadband subscription in total Internet subscription increased from 49.3% in Sep-09

    to 51.3% in Dec-09. 86.54% oftheBroadbandsubscribersareusing Digital Subscriber Line (DSL)

    technology.

    8. Average Revenueper User (ARPU) for GSM-Full Mobility servicedeclinedby 12.4%, from Rs. 164 in

    QE Sep-09 to Rs. 144 in QE Dec-09.

    9. MOU persubscriber for GSM Full mobilityservicedeclinedby 2.82%, from 423 in QE Sep-09 to 411

    in QE Dec-09. The outgoingMOUsdeclinedby 2.67%andincomingby 2.96%.

    10. ARPU for CDMA Full mobilityservicedeclinedby 7%, from Rs. 89 in QE Sep-09 to Rs. 82 in QE Dec-

    09.

    11. MOU per subscriber for CDMA-full mobility service increasedby 3.2% from 308 (QE Sep-09) to

    318 (QE Dec-09). The OutgoingMOUsincreasedby 4.04%and IncomingMOUsby 2.5%.

    12. Gross Revenue (GR)andAdjusted Gross Revenue (AGR) of Telecom Sector for the QE Dec-09 has

    been Rs 39,756.64 Croreand Rs.29, 125.67 Crorerespectively. Therehasbeenan increase of 2.32%and

    0.04%,ascomparedto previous quarter,in GR & AGR respectively.

    13. Average license feeaspercentage ofAGR is 8.34%in Dec-09 asagainst 8.41%inprevious quarter.

    14. The performance ofthe Basic Telephone Service (Wire line) Service Providers is at same

    level as compared to theprevious quarterinrespect oftheparameter of Call completionrate (in

    local network)and Time Taken for Refund ofdepositsafterclosures.

    15. The performance ofthe CellularMobile Telephone Service providers is at same level as

    compared to the previous quarter in respect ofthe parameter of TCH Congestion,Metering and

    billing credibility - post paid and Period ofapplyingcredit/ waiver/ adjustmentto customers

    account fromthedate ofresolution ofcomplaints.

    16. Total Number ofchannelsregisteredwithMinistry of I&Bincreased from 472 in Sep-09 to 485 in

    Dec-09. Thereare 142 pay TV channelsinexistenceasreportedby 23 broadcasters/theirdistributorsat

    the Quarterending Dec-09.

  • 8/7/2019 Business_Statistics_Project2_2010

    12/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    12

    17. Maximum number of TVchannels being carried by any ofthe reportedMSOs is 253 whereas

    in the conventional analogue form,maximumnumber ofchannelsbeingcarriedbythereportedMSOs

    is 100 channels.

    18. Thenumber ofprivate FM Radio stationsin operationremainedas 248 attheend of Dec-09.

    19. Besidesthe free DTH service of Doordarshan,thereare 6 private DTH licensees.All the 6 DTH

    licenseesare offeringpay DTH servicesto thecustomersas on 31.12.2009 andtheirreportedsubscriber

    baseis 19.1 million.

    20. Number of Set TopBoxes (STBs)installedin CAS notifiedareas of Delhi,Mumbai, Kolkataand

    Chennaiincreased from 7, 34,016 in Sep-09 to 7, 45,953 in Dec-09.

  • 8/7/2019 Business_Statistics_Project2_2010

    13/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    13

    4. Research Gap

    5. Objectives

    To determine if the data for individual companies is statistically significant.

    To determine the various statistical parameters for the collected data.

    To compare the difference in population means among the different companies of

    Automobile sector using one way ANOVA on the basis of closing price.

    To compare the difference in population means among the different companies of

    Telecom sector using one way ANOVA on the basis of closing price.To compare the performance of Automobile sector with Telecom sector using one way

    ANOVA on the basis of closing price for past few years.

    6. Hypothesis

    A)For comparing Population Mean among 5 Companies in Automobile Sector using ANOVA

    test:

    Ho: 1= 2= 3= 4= 5. The null hypothesis will be that all population mean of5 companiesof Automobile sector are equal.

    H1:The alternative hypothesis is that at least one mean is different.

    1, 2, 3, 4, 5Population Mean of5 Companies of Automobile Sector.

    B)For comparing Population Mean among 5 Companies in Telecom Sector using ANOVA test:

    Ho: 1= 2= 3= 4= 5. The null hypothesis will be that all population mean of Telecom

    sector companies are equal.

    H1:The alternative hypothesis is that at least one mean is different.

  • 8/7/2019 Business_Statistics_Project2_2010

    14/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    14

    1, 2, 3, 4, 5Population Mean of5 Companies of Telecom Sector

    C)For comparing Population Mean among Automobile & Telecom Sector using ANOVA test:

    Ho: 1= 2. The null hypothesis will be that population of Automobile & Telecom Sector is

    equal.

    H1:1 2. The alternative hypothesis is that at least one mean is different.

    1, 2 Population Mean of Automobile & Telecom Sector respectively.

    7. Methodology

    ANOVA: An Introduction

    In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their

    associated procedures, in which the observed variance is partitioned into components due to

    different sources of variation. In its simplest form ANOVA provides a statistical test of whether

    or not the means of several groups are all equal, and therefore generalizes Student's two-

    samplet-test to more than two groups. ANOVAs are helpful because they possess a certainadvantage over a two-sample t-test. Doing multiple two-sample t-tests would result in a largely

    increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing

    three or more means.

    Tools Used

    yMicrosoft Excel 2007

    yStatistical Package for Social Sciences (SPSS) v.17.0

    Assumption

    1.The populations follow normal distribution.

    2.The populations have equal standard deviations ().

    3.The samples must be independent.

  • 8/7/2019 Business_Statistics_Project2_2010

    15/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    15

    4.We have ignored all factors other than Closing Price while comparing the performance of

    the two sectors.

    A.Study of Statistical Data and their properties(Automobile):

    Table A.1 Descriptive Analysis ofHero Honda

    Column1

    Mean 762.2028707

    StandardError 10.08293663

    Median 697.6

    Mode 750

    Standard Deviation 451.2606994

    Sample Variance 203636.2188

    Kurtosis 1.081689574

    Skewness 1.304590037

    Range 1905.8

    Minimum 183.2

    Maximum 2089

    Sum 1526692.35

    Count 2003

    Largest(1) 2089

    Smallest(1) 183.2

    Confidence Level(95.0%) 19.77414702

    Table A.2 Descriptive Analysis ofHonda Siel

    Column1

    Mean 180.7870504

    StandardError 1.763607757

    Median 158

    Mode 120

  • 8/7/2019 Business_Statistics_Project2_2010

    16/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    16

    Standard Deviation 77.79889317

    Sample Variance 6052.667778

    Kurtosis 4.240306727

    Skewness 1.990727727

    Range 437.4

    Minimum 90.1

    Maximum 527.5

    Sum 351811.6

    Count 1946

    Largest(1) 527.5

    Smallest(1) 90.1

    Confidence

    Level(95.0%) 3.458759947

    Table A.3 Descriptive Analysis ofBajaj

    Column1

    Mean 1175.993251

    StandardError 30.69947011

    Median 1022.8

    Mode 2400

    Standard Deviation 704.0828266

    Sample Variance 495732.6267

    Kurtosis -1.053965374Skewness 0.525862477

    Range 2426.9

    Minimum 300

    Maximum 2726.9

    Sum 618572.45

    Count 526

    Largest(1) 2726.9

    Smallest(1) 300

    Confidence Level(95.0%) 60.30888705

    Table A.4Descriptive Analysis ofMaruti

    Column1

    Mean 760.3957727

    StandardError 8.251784972

  • 8/7/2019 Business_Statistics_Project2_2010

    17/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    17

    Median 743.65

    Mode 412.45

    Standard Deviation 348.7294539

    Sample Variance 121612.232

    Kurtosis -0.276390609

    Skewness 0.668814453

    Range 1534.85

    Minimum 164.05

    Maximum 1698.9

    Sum 1358066.85

    Count 1786

    Largest(1) 1698.9

    Smallest(1) 164.05

    Confidence Level(95.0%) 16.18417491

    Table A.5Descriptive Analysis of Tata Motors

    Column1

    Mean 393.8099162

    StandardError 7.601091444

    Median 435

    Mode 167

    Standard Deviation 143.8193993

    Sample Variance 20684.01963

    Kurtosis -0.858975946

    Skewness -0.279280402

    Range 636.65

    Minimum 113.35

    Maximum 750

    Sum 140983.95

    Count 358

    Largest(1) 750

    Smallest(1) 113.35

    Confidence Level(95.0%) 14.94854308

  • 8/7/2019 Business_Statistics_Project2_2010

    18/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    18

    B.Study of Statistical Data and their properties(Telecom):

    Table B.1Descriptive Analysis of Airtel

    Column1

    Mean 389.9290814

    StandardError 6.404968253

    Median 321.75

    Mode 33.3

    Standard Deviation 300.3513554

    Sample Variance 90210.93668

    Kurtosis -1.146314454

  • 8/7/2019 Business_Statistics_Project2_2010

    19/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    19

    Skewness 0.465762633

    Range 1106

    Minimum 20.75

    Maximum 1126.75

    Sum 857454.05

    Count 2199

    Largest(1) 1126.75

    Smallest(1) 20.75

    Confidence Level(95.0%) 12.56042331

    Table B.2 Descriptive Analysis ofIdea

    Column1

    Mean 83.66429372

    StandardError 0.97526328

    Median 77.675

    Mode 57.8

    Standard Deviation 29.12757304

    Sample Variance 848.4155109

    Kurtosis -1.09520811

    Skewness 0.400761022

    Range 119.15

    Minimum 36.8Maximum 155.95

    Sum 74628.55

    Count 892

    Largest(1) 155.95

    Smallest(1) 36.8

    Confidence Level(95.0%) 1.914080953

    Table B.3 Descriptive Analysis ofMTNL

    Column1

    Mean 120.0458063

    StandardError 0.729248285

    Median 121.6

    Mode 142.5

    Standard Deviation 32.63742531

  • 8/7/2019 Business_Statistics_Project2_2010

    20/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    20

    Sample Variance 1065.201531

    Kurtosis -0.317095349

    Skewness 0.129387344

    Range 166.45

    Minimum 53.35

    Maximum 219.8

    Sum 240451.75

    Count 2003

    Largest(1) 219.8

    Smallest(1) 53.35

    Confidence Level(95.0%) 1.430164974

    Table B.4Descriptive Analysis ofReliance Commn

    Column1

    Mean 362.9861007

    StandardError 5.2003096

    Median 317.05

    Mode 236

    Standard Deviation 170.2654744

    Sample Variance 28990.33178

    Kurtosis -0.562170396

    Skewness 0.615253556

    Range 685.8

    Minimum 132.3

    Maximum 818.1

    Sum 389121.1

    Count 1072

    Largest(1) 818.1

    Smallest(1) 132.3

    Confidence Level(95.0%) 10.20395081

    Table B.5Descriptive Analysis of Tata CommnColumn1

    Mean 20.41194054

    StandardError 0.209730103

    Median 20.3

    Mode 11.5

  • 8/7/2019 Business_Statistics_Project2_2010

    21/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    21

    Standard Deviation 10.46340943

    Sample Variance 109.4829369

    Kurtosis 0.940549971

    Skewness 0.640975784

    Range 59.3

    Minimum 4.35

    Maximum 63.65

    Sum 50805.32

    Count 2489

    Largest(1) 63.65

    Smallest(1) 4.35

    Confidence Level(95.0%) 0.411263509

    C. ANOVA test for comparing Population Mean among 5 Companies in AutomobileSector:

    Table C-Comparison of various Automobile Companies on basis of their Stock Prices:

    Anova: Single Factor

    SUMMARY

    Groups Count Sum Average Variance

    Column 1 526 618572.5 1175.993 495732.6

    Column 2 2003 1526692 762.2029 203636.2

    Column 3 1946 351811.6 180.7871 6052.668

    Column 4 1786 1358067 760.3958 121612.2

    ANOVA

    Source of Variation SS Df MS F P-value F crit

    Between Groups 6.14E+08 3 2.05E+08 1427.039 0 2.606328

    Within Groups 8.97E+08 6257 143325.8

    Total 1.51E+09 6260

    D. ANOVA test for comparing Population Mean among 5 Companies in Telecom Sector:

  • 8/7/2019 Business_Statistics_Project2_2010

    22/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    22

    Table D-Comparison of various Telecom Companies on basis of their Stock Prices:

    Anova:

    SingleFactor

    SUMMARY

    Groups Count Sum Average Variance

    Column 1 892 74628.55 83.66429372 848.4155109

    Column 2 2003 240451.75 120.0458063 1065.201531

    Column 3 1072 389121.1 362.9861007 28990.33178

    Column 4 2489 50805.32 20.41194054 109.4829369

    ANOVA

    Source of Variation SS Df MS F P-value F crit

    Between Groups 89096148 3 29698716.05 5601.252775 0 2.606285

    Within Groups 34209511 6452 5302.156008

    Total 1.23E+08 6455

    E. ANOVA test for comparing Population Mean among Automobile & Telecom Sector:

    Table E-Comparison of various Automobile & Telecom Sectors on basis of their Stock Prices:

    Anova: Single Factor

    SUMMARY

    Groups Count Sum Average Variance

  • 8/7/2019 Business_Statistics_Project2_2010

    23/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    23

    Column 1 334 349339 1045.925 58319.42

    Column 2 419 70330.03 167.8521 2187.667

    ANOVA

    Source of

    Variation SS df MS F P-value F crit

    Between Groups 1.43E+08 1 1.43E+08 5292.083 0 3.853871

    Within Groups 20334812 751 27076.98

    Total 1.64E+08 752

    8. Data Analysis

    A.Study of Statistical Data and their properties(Automobile):

    Table A.1Descriptive Analysis ofHero Honda

    Factor Value Interpretation

    Skewness 1.304590037 Positive Skewed Curve

    Kurtosis 1.081689574 Mesokurtic Curve

    Table A.2 Descriptive Analysis ofHonda Siel

    Factor Value Interpretation

    Skewness 1.990727727 Positive Skewed Curve

    Kurtosis 4.240306727 Leptokurtic

    Table A.3 Descriptive Analysis ofBajaj

    Factor Value Interpretation

    Skewness 0.525862477 Positive Skewed Curve

    Kurtosis -1.053965374 Mesokurtic

    Table A.4Descriptive Analysis ofMaruti

    Factor Value Interpretation

    Skewness 0.668814453 Positive Skewed Curve

  • 8/7/2019 Business_Statistics_Project2_2010

    24/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    24

    Kurtosis -0.276390609 Mesokurtic

    Table A.5Descriptive Analysis of Tata Motors

    Factor Value Interpretation

    Skewness -0.279280402 Negative Skewed Curve

    Kurtosis -0.858975946 Mesokurtic

    B.Study of Statistical Data and their properties(Telecom):

    Table B.1Descriptive Analysis of Airtel

    Factor Value Interpretation

    Skewness 0.465762633 Positive Skewed Curve

    Kurtosis -1.146314454 Mesokurtic

    Table B.2 Descriptive Analysis ofIdea

    Factor Value Interpretation

    Skewness 0.400761022 Positive Skewed Curve

    Kurtosis -1.09520811 Mesokurtic

    Table B.3 Descriptive Analysis ofMTNL

    Factor Value Interpretation

    Skewness 0.129387344 Positive Skewed Curve

    Kurtosis 0.317095349 Mesokurtic

    Table B.4Descriptive Analysis ofReliance Commn

    Factor Value Interpretation

    Skewness 0.615253556 Positive Skewed Curve

    Kurtosis -0.562170396

    Table B.5Descriptive Analysis of Tata Commn

  • 8/7/2019 Business_Statistics_Project2_2010

    25/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    25

    Factor Value Interpretation

    Skewness 0.640975784 Positive Skewed Curve

    Kurtosis 0.940549971 Mesokurtic

    C. ANOVA test for comparing Population Mean among 5 Companies in Automobile Sector:

    From Table-C, As F Calculated (1427.039) is greater than F-critical (2.606328) & p-value (0) is

    less than (0.05), Hence Null Hypothesis is Rejected and there is significant difference in the

    Variance between the 5 companies of Automobile Sector.

    D. ANOVA test for comparing Population Mean among 5 Companies in Telecom Sector:

    From Table-D, As F Calculated (5601.252775) is greater than F-critical (2.606285) & p-value (0)

    is less than (0.05), Hence Null Hypothesis is Rejected and there is significant difference in the

    Variance between the 5 companies of Telecom Sector.

    E. ANOVA test for comparing Population Mean among Automobile & Telecom Sector:

    From Table-E, As F Calculated (5292.083) is greater than F-critical (3.853871) & p-value (0) isless than (0.05), Hence Null Hypothesis is Rejected and there is significant difference in the

    Variance between Automobile & Telecom Sector.

    9. Policy Implications

    10. Conclusion

    11. Recommendation

  • 8/7/2019 Business_Statistics_Project2_2010

    26/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    26

    12. Bibliography

    References

    1.www.mu.ac.in/arts/social_science/eco/pdfs/depart/dwp3.pdf

    2.http://www.trade.gov/static/India%20White%20Paper.pdf

    3.http://gdrdeveloppementtransition.org/colloque_2008/RICHET-RUET.pdf

    4.http://www.iaeng.org/publication/WCE2009/WCE2009_pp1147-1152.pdf

    5.http://www.careratings.com/current/3/7683.pdf

    6.http://gaj-india.com/usefulupdates/indiantelecom%20june%202010.pdf

    7.http://www.iimahd.ernet.in/ctps/telecomsector.htm, last accessed on 19th August 2010.

    8.http://www.economywatch.com/business-and-economy/automobile-industry.html , last

    accessed on 19th

    August 2010.

  • 8/7/2019 Business_Statistics_Project2_2010

    27/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    27

    TABLES:

    TABLE NO CONTENT

    Table T.1 Closing Stock Price ofHero Honda from 12-08-2002 to 16-08-2010

    Table T.2 Closing Stock Price ofHero Siel from 1-01-2003 to 16-08-2010

    Table T.3 Closing Stock Price ofBajaj from 25-05-2008 to 16-08-2010

    Table T.4 Closing Stock Price ofMaruti Suzuki from 9-07-2003 to 16-08-2010

    Table T.5 Closing Stock Price of Tata from 5-11-2008 to 16-08-2010

    Table T.6 Closing Stock Price of Airtel from 20-02-2002 to 16-08-2010

    Table T.7 Closing Stock Price ofIdea from 9-03-2007 to 16-08-2010

    Table T.8 Closing Stock Price ofMTNL from 12-08-2002 to 16-08-2010

    Table T.9 Closing Stock Price ofReliance Commn from 6-03-2006 to 16-08-2010

    Table T.10 Closing Stock Price of Tata from 27-10-2000 to 16-08-2010

    Table T.11

    ANOVA Analysis table for Comparing Automobile with Telecom from 31-12-2008 to 16-08-2010

    Table T.12ANOVA Analysis table for Comparing Telecom with Automobile from 31-12-2008 to 16-08-

    2010

  • 8/7/2019 Business_Statistics_Project2_2010

    28/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    28

    Table T.1-Closing Stock Price ofHero Honda from 12-08-2002 to 16-08-2010

    Date Close

    16-08-2010 1890.05

    13-08-2010 1887.35

    12-08-2010 1865.1

    11-08-2010 1864.8

    10-08-2010 1867

    09-08-2010 1865

    06-08-2010 1836

    05-08-2010 1862

    04-08-2010 1876.25

    03-08-2010 1862

    02-08-2010 1826

    30-07-2010 1814.9

    29-07-2010 1870

    28-07-2010 1852.8

    27-07-2010 1863.05

    26-07-2010 1807

    23-07-2010 1948.4

    22-07-2010 1949

    21-07-2010 1941

    20-07-2010 1945

    19-07-2010 1959

    16-07-2010 1978

    15-07-2010 1975

    14-07-2010 1986

    13-07-2010 1980

    12-07-2010 1990

    09-07-2010 2017

    08-07-2010 1996

    07-07-2010 2000

  • 8/7/2019 Business_Statistics_Project2_2010

    29/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    29

    06-07-2010 2010

    05-07-2010 2024

    02-07-2010 2023

    01-07-2010 2020

    30-06-2010 2043.3

    29-06-2010 2044.1

    28-06-2010 2042.5

    25-06-2010 2050

    24-06-2010 2050

    23-06-2010 2035

    22-06-2010 2021

    21-06-2010 2021.25

    18-06-2010 2022

    17-06-2010 1982.6

    16-06-2010 2011.2

    15-06-2010 2018

    14-06-2010 2007.8

    11-06-2010 2013.8

    10-06-2010 2010.1

    09-06-2010 1922

    08-06-2010 1937

    07-06-2010 1991.15

    04-06-2010 1995

    03-06-2010 1980

    02-06-2010 1997.9

    01-06-2010 1929

    31-05-2010 1947.45

    28-05-2010 1920

    27-05-2010 1883

    26-05-2010 1890

    25-05-2010 1869.5

    24-05-2010 1894

    21-05-2010 1855

    20-05-2010 187019-05-2010 1865

    18-05-2010 1831.85

    17-05-2010 1852

    14-05-2010 1873

    13-05-2010 1898.2

    12-05-2010 1898

  • 8/7/2019 Business_Statistics_Project2_2010

    30/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    30

    11-05-2010 1893.9

    10-05-2010 1887

    07-05-2010 1885.55

    06-05-2010 1902

    05-05-2010 1886

    04-05-2010 1925

    03-05-2010 1918

    30-04-2010 1909

    29-04-2010 1832.1

    28-04-2010 1848

    27-04-2010 1861.5

    26-04-2010 1865

    23-04-2010 1880.1

    22-04-2010 1912.7

    21-04-2010 1887.3

    20-04-2010 1852.85

    19-04-2010 1895.45

    16-04-2010 1925.6

    15-04-2010 1953

    13-04-2010 1975.1

    12-04-2010 2089

    09-04-2010 2062.9

    08-04-2010 2024

    07-04-2010 2046

    06-04-2010 2035.35

    05-04-2010 2059

    01-04-2010 1946

    31-03-2010 1948.9

    30-03-2010 1965

    29-03-2010 2006

    26-03-2010 2007.55

    25-03-2010 2040

    23-03-2010 1939.05

    22-03-2010 1950.2519-03-2010 1966

    18-03-2010 1940

    17-03-2010 1930

    16-03-2010 1911.35

    15-03-2010 1910.65

    12-03-2010 1918

  • 8/7/2019 Business_Statistics_Project2_2010

    31/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    31

    11-03-2010 1908.25

    10-03-2010 1954

    09-03-2010 1876

    08-03-2010 1912.85

    05-03-2010 1874

    04-03-2010 1801.7

    03-03-2010 1811

    02-03-2010 1793

    26-02-2010 1798

    25-02-2010 1700

    24-02-2010 1676

    23-02-2010 1701

    22-02-2010 1709

    19-02-2010 1681.4

    18-02-2010 1701.9

    17-02-2010 1693.25

    16-02-2010 1701

    15-02-2010 1705

    11-02-2010 1670

    19-01-2010 1660.05

    18-01-2010 1693.9

    15-01-2010 1622.1

    14-01-2010 1617

    13-01-2010 1627

    12-01-2010 1646.1

    11-01-2010 1680

    08-01-2010 1659

    07-01-2010 1650

    06-01-2010 1694.05

    05-01-2010 1715

    04-01-2010 1713.95

    31-12-2009 1723.7

    30-12-2009 1705.5

    29-12-2009 1743.7524-12-2009 1735.1

    23-12-2009 1697.6

    22-12-2009 1704

    21-12-2009 1670

    18-12-2009 1678

    17-12-2009 1670

  • 8/7/2019 Business_Statistics_Project2_2010

    32/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    32

    16-12-2009 1665.1

    15-12-2009 1666.8

    14-12-2009 1687

    11-12-2009 1673

    10-12-2009 1674.1

    09-12-2009 1703.5

    08-12-2009 1673

    07-12-2009 1678

    04-12-2009 1674.95

    03-12-2009 1693.4

    02-12-2009 1704

    01-12-2009 1738.1

    30-11-2009 1720

    27-11-2009 1758.7

    26-11-2009 1740

    25-11-2009 1732.05

    24-11-2009 1689.1

    23-11-2009 1647.3

    20-11-2009 1647.2

    19-11-2009 1637

    18-11-2009 1667

    17-11-2009 1680.9

    16-11-2009 1648

    13-11-2009 1574.9

    12-11-2009 1521.1

    11-11-2009 1516

    10-11-2009 1485

    09-11-2009 1557

    06-11-2009 1530

    05-11-2009 1568

    04-11-2009 1525.05

    03-11-2009 1516

    30-10-2009 1565

    29-10-2009 155028-10-2009 1584

    27-10-2009 1587.5

    26-10-2009 1595

    23-10-2009 1585

    22-10-2009 1590.05

    21-10-2009 1609.2

  • 8/7/2019 Business_Statistics_Project2_2010

    33/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    33

    20-10-2009 1647.6

    16-10-2009 1650

    15-10-2009 1655.2

    14-10-2009 1643

    12-10-2009 1635

    09-10-2009 1645

    08-10-2009 1657.55

    07-10-2009 1642

    06-10-2009 1644.95

    05-10-2009 1644

    01-10-2009 1633

    30-09-2009 1685.1

    29-09-2009 1653.05

    25-09-2009 1644.5

    24-09-2009 1663

    23-09-2009 1681

    22-09-2009 1688

    18-09-2009 1680

    17-09-2009 1655

    16-09-2009 1674

    15-09-2009 1614

    14-09-2009 1569.6

    11-09-2009 1570.15

    10-09-2009 1570

    09-09-2009 1626.85

    08-09-2009 1671.7

    07-09-2009 1631

    04-09-2009 1610

    03-09-2009 1545.1

    02-09-2009 1567.5

    01-09-2009 1535

    31-08-2009 1515

    28-08-2009 1508.5

    27-08-2009 147626-08-2009 1498.9

    25-08-2009 1512.8

    24-08-2009 1523.1

    17-08-2009 1394.8

    14-08-2009 1478.25

    13-08-2009 1508

  • 8/7/2019 Business_Statistics_Project2_2010

    34/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    34

    12-08-2009 1431.35

    11-08-2009 1424.7

    10-08-2009 1423.95

    07-08-2009 1479

    06-08-2009 1518.95

    05-08-2009 1600.95

    04-08-2009 1620.3

    03-08-2009 1625

    31-07-2009 1599.95

    30-07-2009 1633.05

    29-07-2009 1636

    28-07-2009 1676

    27-07-2009 1685

    24-07-2009 1731.7

    23-07-2009 1665

    22-07-2009 1614.55

    21-07-2009 1640.95

    20-07-2009 1639

    17-07-2009 1641

    16-07-2009 1536

    15-07-2009 1490

    14-07-2009 1400.05

    13-07-2009 1400

    10-07-2009 1448.9

    09-07-2009 1472.5

    08-07-2009 1460

    07-07-2009 1436.5

    06-07-2009 1355.5

    03-07-2009 1365.9

    02-07-2009 1375.15

    01-07-2009 1396

    30-06-2009 1395.05

    29-06-2009 1382

    26-06-2009 1410.525-06-2009 1428

    24-06-2009 1454.65

    23-06-2009 1431

    22-06-2009 1474.3

    19-06-2009 1466.1

    18-06-2009 1452

  • 8/7/2019 Business_Statistics_Project2_2010

    35/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    35

    17-06-2009 1355.05

    16-06-2009 1415

    15-06-2009 1419.55

    12-06-2009 1465

    11-06-2009 1475.2

    10-06-2009 1490

    09-06-2009 1488

    08-06-2009 1450

    05-06-2009 1460

    04-06-2009 1354

    03-06-2009 1382.75

    02-06-2009 1381

    01-06-2009 1365.8

    29-05-2009 1335

    28-05-2009 1322

    27-05-2009 1357.9

    26-05-2009 1345

    25-05-2009 1321.5

    22-05-2009 1295

    21-05-2009 1258.1

    20-05-2009 1289

    19-05-2009 1315

    18-05-2009 1487.3

    15-05-2009 1223.15

    14-05-2009 1213.05

    13-05-2009 1192

    12-05-2009 1191

    11-05-2009 1216.3

    08-05-2009 1228.85

    07-05-2009 1221

    06-05-2009 1206

    05-05-2009 1194

    04-05-2009 1199

    29-04-2009 1184.928-04-2009 1127.9

    27-04-2009 1130

    24-04-2009 1143

    23-04-2009 1122.15

    22-04-2009 1082

    21-04-2009 1097.1

  • 8/7/2019 Business_Statistics_Project2_2010

    36/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    36

    20-04-2009 1125.1

    17-04-2009 1116

    16-04-2009 1076.5

    15-04-2009 1070

    13-04-2009 1055

    09-04-2009 1063.15

    08-04-2009 1094

    06-04-2009 1069.8

    02-04-2009 1030

    01-04-2009 1030

    31-03-2009 1072.1

    30-03-2009 1044

    27-03-2009 1085

    26-03-2009 1016.05

    25-03-2009 1013

    24-03-2009 1003.9

    23-03-2009 993.9

    20-03-2009 999

    19-03-2009 989.95

    18-03-2009 1002.45

    17-03-2009 982

    16-03-2009 964.2

    13-03-2009 964

    12-03-2009 970

    09-03-2009 932

    06-03-2009 927.5

    05-03-2009 938.8

    04-03-2009 933.6

    03-03-2009 901

    02-03-2009 896

    27-02-2009 935.5

    26-02-2009 930

    25-02-2009 897.5

    24-02-2009 901.320-02-2009 919.95

    19-02-2009 931.9

    18-02-2009 932

    17-02-2009 950

    16-02-2009 930

    13-02-2009 932.95

  • 8/7/2019 Business_Statistics_Project2_2010

    37/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    37

    12-02-2009 919.95

    11-02-2009 906

    10-02-2009 888

    09-02-2009 892

    06-02-2009 880

    05-02-2009 873.05

    04-02-2009 875.9

    03-02-2009 878.1

    02-02-2009 876.35

    30-01-2009 876.5

    29-01-2009 875

    28-01-2009 870.15

    27-01-2009 857

    23-01-2009 848.6

    22-01-2009 849

    21-01-2009 838

    20-01-2009 834.8

    19-01-2009 840

    16-01-2009 847

    15-01-2009 830.2

    14-01-2009 829.9

    13-01-2009 808.5

    12-01-2009 780

    09-01-2009 799.8

    07-01-2009 773.5

    06-01-2009 792.25

    05-01-2009 777

    02-01-2009 790

    01-01-2009 809

    31-12-2008 802.25

    30-12-2008 811

    29-12-2008 805

    26-12-2008 791

    24-12-2008 81323-12-2008 809

    22-12-2008 802.8

    19-12-2008 817.2

    18-12-2008 822.75

    17-12-2008 804

    16-12-2008 810

  • 8/7/2019 Business_Statistics_Project2_2010

    38/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    38

    15-12-2008 792.25

    12-12-2008 775.15

    11-12-2008 793.5

    10-12-2008 793.2

    08-12-2008 788

    05-12-2008 762.75

    04-12-2008 750

    03-12-2008 744.9

    02-12-2008 758

    01-12-2008 759.95

    28-11-2008 800

    26-11-2008 780

    25-11-2008 739

    24-11-2008 730

    21-11-2008 735.15

    20-11-2008 713.25

    19-11-2008 739.9

    18-11-2008 725

    17-11-2008 718

    14-11-2008 737.95

    12-11-2008 753.05

    11-11-2008 750

    10-11-2008 760

    07-11-2008 750

    06-11-2008 723

    05-11-2008 745

    04-11-2008 736.1

    03-11-2008 729.25

    31-10-2008 745

    29-10-2008 752.75

    28-10-2008 735

    27-10-2008 708

    24-10-2008 734

    23-10-2008 767.0522-10-2008 816.45

    21-10-2008 826

    20-10-2008 805.75

    17-10-2008 827

    16-10-2008 845.05

    15-10-2008 829

  • 8/7/2019 Business_Statistics_Project2_2010

    39/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    39

    14-10-2008 815.1

    13-10-2008 831

    10-10-2008 818.8

    08-10-2008 884.25

    07-10-2008 872

    06-10-2008 860.25

    03-10-2008 890

    01-10-2008 869.95

    30-09-2008 873

    29-09-2008 840.15

    26-09-2008 850

    25-09-2008 855

    24-09-2008 844.95

    23-09-2008 830.8

    22-09-2008 817.9

    19-09-2008 822.15

    18-09-2008 840

    17-09-2008 816.1

    16-09-2008 855

    15-09-2008 825.2

    12-09-2008 835

    11-09-2008 834

    10-09-2008 837.5

    09-09-2008 828.55

    08-09-2008 855

    05-09-2008 860

    04-09-2008 878

    02-09-2008 857.4

    01-09-2008 845

    29-08-2008 825

    28-08-2008 813

    27-08-2008 809.2

    26-08-2008 797.05

    25-08-2008 804.5522-08-2008 797.1

    21-08-2008 803

    20-08-2008 805

    19-08-2008 796.05

    18-08-2008 790.1

    14-08-2008 785.8

  • 8/7/2019 Business_Statistics_Project2_2010

    40/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    40

    13-08-2008 812

    12-08-2008 820

    11-08-2008 829.85

    08-08-2008 820

    07-08-2008 819

    06-08-2008 823

    05-08-2008 826.25

    04-08-2008 795.15

    01-08-2008 797

    31-07-2008 788.05

    30-07-2008 778

    29-07-2008 729

    28-07-2008 760

    25-07-2008 758

    24-07-2008 762

    23-07-2008 750

    22-07-2008 729.8

    21-07-2008 723

    18-07-2008 683

    17-07-2008 657.2

    16-07-2008 635

    15-07-2008 654.65

    14-07-2008 660

    11-07-2008 664.05

    10-07-2008 688

    09-07-2008 743

    08-07-2008 685.5

    07-07-2008 699

    04-07-2008 667.35

    03-07-2008 651.6

    02-07-2008 674.8

    01-07-2008 682

    30-06-2008 685

    27-06-2008 68426-06-2008 748

    25-06-2008 695.35

    24-06-2008 707

    23-06-2008 735

    20-06-2008 760

    19-06-2008 808

  • 8/7/2019 Business_Statistics_Project2_2010

    41/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    41

    18-06-2008 782.25

    17-06-2008 775.6

    16-06-2008 763

    13-06-2008 788

    12-06-2008 808

    11-06-2008 835

    10-06-2008 774

    06-06-2008 759.5

    05-06-2008 769

    04-06-2008 785

    03-06-2008 798

    02-06-2008 779

    30-05-2008 752

    29-05-2008 770

    28-05-2008 795.15

    27-05-2008 790

    26-05-2008 792

    23-05-2008 800

    22-05-2008 787.1

    21-05-2008 785

    20-05-2008 803

    16-05-2008 807.25

    15-05-2008 807.7

    14-05-2008 819.85

    13-05-2008 803

    12-05-2008 798.2

    09-05-2008 812.05

    08-05-2008 815

    07-05-2008 819

    06-05-2008 817

    05-05-2008 818.1

    02-05-2008 843.1

    30-04-2008 853.95

    29-04-2008 857.0528-04-2008 818.5

    25-04-2008 812.25

    24-04-2008 780

    23-04-2008 748

    22-04-2008 758

    21-04-2008 746.1

  • 8/7/2019 Business_Statistics_Project2_2010

    42/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    42

    17-04-2008 740

    16-04-2008 742

    15-04-2008 740

    11-04-2008 740

    10-04-2008 746

    09-04-2008 745

    08-04-2008 737.05

    07-04-2008 750

    04-04-2008 762.5

    03-04-2008 751

    02-04-2008 740

    01-04-2008 707

    31-03-2008 689.9

    28-03-2008 719

    27-03-2008 686.25

    26-03-2008 679.75

    25-03-2008 675.05

    19-03-2008 657

    18-03-2008 680.1

    14-03-2008 711

    13-03-2008 737

    12-03-2008 732.9

    11-03-2008 734.25

    10-03-2008 758

    07-03-2008 764.45

    05-03-2008 775

    04-03-2008 773.15

    03-03-2008 775

    29-02-2008 762

    28-02-2008 750

    27-02-2008 718

    26-02-2008 738.95

    25-02-2008 740

    22-02-2008 71521-02-2008 730

    20-02-2008 724.7

    19-02-2008 720.2

    18-02-2008 719

    15-02-2008 732.05

    14-02-2008 730

  • 8/7/2019 Business_Statistics_Project2_2010

    43/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    43

    13-02-2008 720

    12-02-2008 674.75

    11-02-2008 683

    08-02-2008 709.9

    07-02-2008 710

    06-02-2008 719.85

    05-02-2008 732

    04-02-2008 757

    01-02-2008 725.05

    31-01-2008 682

    30-01-2008 697

    29-01-2008 686

    28-01-2008 694.75

    25-01-2008 696

    24-01-2008 650

    23-01-2008 606

    22-01-2008 582

    21-01-2008 652.9

    18-01-2008 696

    17-01-2008 696.95

    16-01-2008 692

    15-01-2008 706

    14-01-2008 705

    11-01-2008 662

    10-01-2008 684

    09-01-2008 688

    08-01-2008 691.3

    07-01-2008 702

    04-01-2008 699.45

    03-01-2008 710

    02-01-2008 696

    01-01-2008 698

    31-12-2007 697

    28-12-2007 69927-12-2007 705

    26-12-2007 701

    24-12-2007 700

    20-12-2007 700

    19-12-2007 706.5

    18-12-2007 706

  • 8/7/2019 Business_Statistics_Project2_2010

    44/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    44

    17-12-2007 708.5

    14-12-2007 714

    13-12-2007 715

    12-12-2007 703

    11-12-2007 701

    10-12-2007 690.25

    07-12-2007 690

    06-12-2007 688.8

    05-12-2007 698

    04-12-2007 697.05

    03-12-2007 705

    30-11-2007 723

    29-11-2007 741.8

    28-11-2007 705.25

    27-11-2007 727

    26-11-2007 726

    23-11-2007 715

    22-11-2007 708

    21-11-2007 710

    20-11-2007 696.05

    19-11-2007 708

    16-11-2007 696

    15-11-2007 689

    14-11-2007 672

    13-11-2007 662

    12-11-2007 660

    09-11-2007 662

    08-11-2007 675

    07-11-2007 670

    06-11-2007 667.5

    05-11-2007 668

    02-11-2007 673

    01-11-2007 687

    31-10-2007 72530-10-2007 727.9

    29-10-2007 744.95

    26-10-2007 737

    25-10-2007 740.1

    24-10-2007 738

    23-10-2007 751

  • 8/7/2019 Business_Statistics_Project2_2010

    45/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    45

    22-10-2007 757.95

    19-10-2007 752

    18-10-2007 730

    17-10-2007 738.1

    16-10-2007 752.05

    15-10-2007 768

    12-10-2007 756

    11-10-2007 752

    10-10-2007 757

    09-10-2007 746

    08-10-2007 730

    05-10-2007 722

    04-10-2007 720.1

    03-10-2007 734

    01-10-2007 732

    28-09-2007 741.1

    27-09-2007 740

    26-09-2007 740.95

    25-09-2007 744.9

    24-09-2007 770

    21-09-2007 731

    20-09-2007 711

    19-09-2007 704

    18-09-2007 676.85

    17-09-2007 664.1

    14-09-2007 668.5

    13-09-2007 668.95

    12-09-2007 657

    11-09-2007 659

    10-09-2007 661

    07-09-2007 668.9

    06-09-2007 655

    05-09-2007 635.35

    04-09-2007 642.103-09-2007 645

    31-08-2007 649

    30-08-2007 648.5

    29-08-2007 634

    28-08-2007 631.5

    27-08-2007 638

  • 8/7/2019 Business_Statistics_Project2_2010

    46/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    46

    24-08-2007 638.2

    23-08-2007 623

    22-08-2007 628.5

    21-08-2007 634

    20-08-2007 644

    17-08-2007 625

    16-08-2007 644

    14-08-2007 652

    13-08-2007 658.5

    10-08-2007 656.95

    09-08-2007 679.6

    08-08-2007 679

    07-08-2007 654.3

    06-08-2007 649.45

    03-08-2007 655.45

    02-08-2007 652.25

    01-08-2007 668.25

    31-07-2007 674.05

    30-07-2007 685.05

    27-07-2007 683.6

    26-07-2007 716.95

    25-07-2007 698.9

    24-07-2007 697.4

    23-07-2007 708.95

    20-07-2007 684.1

    19-07-2007 694.1

    18-07-2007 719.1

    17-07-2007 700.05

    16-07-2007 685.2

    13-07-2007 678.8

    12-07-2007 673.4

    11-07-2007 669.7

    10-07-2007 670.45

    09-07-2007 687.706-07-2007 699.3

    05-07-2007 688.15

    04-07-2007 685.45

    03-07-2007 689.25

    02-07-2007 691.8

    29-06-2007 692.6

  • 8/7/2019 Business_Statistics_Project2_2010

    47/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    47

    28-06-2007 678.75

    27-06-2007 676.7

    26-06-2007 670.15

    25-06-2007 670.4

    22-06-2007 668.4

    21-06-2007 663.1

    20-06-2007 669.4

    19-06-2007 666.1

    18-06-2007 654.35

    15-06-2007 680.05

    14-06-2007 682.95

    13-06-2007 694.7

    12-06-2007 704.5

    11-06-2007 698.6

    08-06-2007 684.6

    07-06-2007 701.2

    06-06-2007 716.35

    05-06-2007 716.1

    04-06-2007 712.5

    31-05-2007 732.4

    30-05-2007 697.25

    29-05-2007 688.65

    28-05-2007 682.25

    25-05-2007 679.2

    24-05-2007 674.85

    23-05-2007 690.2

    22-05-2007 689.95

    21-05-2007 681.85

    18-05-2007 685.55

    17-05-2007 678.3

    16-05-2007 677.85

    15-05-2007 697.6

    14-05-2007 688.1

    11-05-2007 704.810-05-2007 706.95

    09-05-2007 700.15

    08-05-2007 679.7

    07-05-2007 706.05

    04-05-2007 699.45

    03-05-2007 704.3

  • 8/7/2019 Business_Statistics_Project2_2010

    48/430

  • 8/7/2019 Business_Statistics_Project2_2010

    49/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    49

    28-02-2007 677.75

    27-02-2007 687.2

    26-02-2007 698.95

    23-02-2007 706.3

    22-02-2007 715.5

    21-02-2007 740.45

    20-02-2007 718.45

    15-02-2007 745.5

    14-02-2007 711.55

    13-02-2007 720.35

    12-02-2007 733.25

    09-02-2007 726.1

    08-02-2007 728.15

    07-02-2007 738.95

    06-02-2007 719.55

    05-02-2007 731.35

    02-02-2007 716.25

    01-02-2007 725.7

    31-01-2007 716.3

    29-01-2007 716.05

    25-01-2007 717

    24-01-2007 719.25

    23-01-2007 717.1

    22-01-2007 724.35

    19-01-2007 729.85

    18-01-2007 730.3

    17-01-2007 728.85

    16-01-2007 726.55

    15-01-2007 734.1

    12-01-2007 743.15

    11-01-2007 733.05

    10-01-2007 730.1

    09-01-2007 730.3

    08-01-2007 733.705-01-2007 749.95

    04-01-2007 755.4

    03-01-2007 778.3

    02-01-2007 785.45

    29-12-2006 763.7

    28-12-2006 760.25

  • 8/7/2019 Business_Statistics_Project2_2010

    50/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    50

    27-12-2006 746.35

    26-12-2006 748.35

    22-12-2006 750.25

    21-12-2006 729.75

    20-12-2006 725.25

    19-12-2006 753.95

    18-12-2006 750.65

    15-12-2006 737

    14-12-2006 712.2

    13-12-2006 718.6

    12-12-2006 724.9

    11-12-2006 738.8

    08-12-2006 745.35

    07-12-2006 750.45

    06-12-2006 767.75

    05-12-2006 768.65

    04-12-2006 765

    01-12-2006 771.15

    30-11-2006 742.25

    29-11-2006 744.35

    28-11-2006 741.5

    27-11-2006 736.55

    24-11-2006 739.85

    23-11-2006 748.75

    22-11-2006 730.15

    21-11-2006 709.5

    20-11-2006 708.3

    17-11-2006 694.9

    16-11-2006 709.4

    15-11-2006 713.7

    14-11-2006 706.35

    13-11-2006 714.5

    10-11-2006 725.55

    09-11-2006 717.308-11-2006 712.5

    07-11-2006 742.55

    06-11-2006 760.85

    03-11-2006 761.05

    02-11-2006 766.05

    01-11-2006 765.2

  • 8/7/2019 Business_Statistics_Project2_2010

    51/430

  • 8/7/2019 Business_Statistics_Project2_2010

    52/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    52

    30-08-2006 720.4

    29-08-2006 719.3

    28-08-2006 715.35

    25-08-2006 714.2

    24-08-2006 713.4

    23-08-2006 700.15

    22-08-2006 705.35

    21-08-2006 697.6

    18-08-2006 706.2

    17-08-2006 693.65

    16-08-2006 705.15

    14-08-2006 682.55

    11-08-2006 695.95

    10-08-2006 674.3

    09-08-2006 678.1

    08-08-2006 668.95

    07-08-2006 669.9

    04-08-2006 688.1

    02-08-2006 696.65

    01-08-2006 696.8

    31-07-2006 705.9

    28-07-2006 698.3

    27-07-2006 692

    26-07-2006 704

    25-07-2006 712.7

    24-07-2006 712.15

    21-07-2006 709.6

    20-07-2006 715.9

    19-07-2006 713.9

    18-07-2006 719.2

    17-07-2006 709.75

    14-07-2006 717.75

    13-07-2006 711.15

    12-07-2006 728.711-07-2006 721.25

    10-07-2006 766.8

    07-07-2006 748.15

    06-07-2006 776.4

    05-07-2006 792.35

    04-07-2006 792.35

  • 8/7/2019 Business_Statistics_Project2_2010

    53/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    53

    03-07-2006 790.9

    30-06-2006 793.65

    29-06-2006 787.8

    28-06-2006 756.8

    27-06-2006 751.1

    26-06-2006 733.4

    23-06-2006 759.45

    22-06-2006 769.8

    21-06-2006 756.15

    20-06-2006 747.75

    19-06-2006 743.9

    14-06-2006 642.65

    13-06-2006 656.7

    12-06-2006 705.3

    09-06-2006 751.8

    08-06-2006 735.9

    07-06-2006 739.1

    06-06-2006 756.6

    05-06-2006 755.35

    02-06-2006 762.65

    01-06-2006 719.9

    31-05-2006 801.8

    30-05-2006 801.8

    29-05-2006 848.2

    26-05-2006 826.1

    25-05-2006 792.7

    24-05-2006 773.25

    23-05-2006 793.65

    22-05-2006 813.8

    19-05-2006 823.4

    18-05-2006 872.9

    17-05-2006 892.65

    16-05-2006 848.5

    15-05-2006 853.3512-05-2006 879.2

    11-05-2006 871.1

    10-05-2006 879.75

    09-05-2006 881

    08-05-2006 876.5

    05-05-2006 858.2

  • 8/7/2019 Business_Statistics_Project2_2010

    54/430

  • 8/7/2019 Business_Statistics_Project2_2010

    55/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    55

    09-03-2006 880.6

    08-03-2006 901

    07-03-2006 887.85

    06-03-2006 884.3

    03-03-2006 879.65

    02-03-2006 900.25

    01-03-2006 896.4

    28-02-2006 889.3

    27-02-2006 887.85

    24-02-2006 889.45

    23-02-2006 913.8

    22-02-2006 897.3

    21-02-2006 885.4

    20-02-2006 885.4

    17-02-2006 889.1

    16-02-2006 921.25

    15-02-2006 893

    14-02-2006 903.75

    13-02-2006 906.75

    10-02-2006 922.7

    09-02-2006 885.05

    08-02-2006 885.05

    07-02-2006 874.15

    06-02-2006 870.6

    03-02-2006 849.3

    02-02-2006 859.2

    01-02-2006 864.75

    31-01-2006 857.2

    30-01-2006 850.85

    27-01-2006 876.85

    26-01-2006 862.25

    25-01-2006 862.25

    24-01-2006 838.15

    23-01-2006 835.7520-01-2006 841.65

    19-01-2006 841.65

    18-01-2006 832.25

    17-01-2006 841

    16-01-2006 841

    13-01-2006 838.75

  • 8/7/2019 Business_Statistics_Project2_2010

    56/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    56

    12-01-2006 842.65

    11-01-2006 846.3

    10-01-2006 846.3

    09-01-2006 873.2

    06-01-2006 877.25

    05-01-2006 867.95

    04-01-2006 856.65

    03-01-2006 861.25

    02-01-2006 846.1

    30-12-2005 859.2

    29-12-2005 845.45

    28-12-2005 851.55

    27-12-2005 862.5

    26-12-2005 849.8

    23-12-2005 853.3

    22-12-2005 870.15

    21-12-2005 874.65

    20-12-2005 840.15

    19-12-2005 855.25

    16-12-2005 846.95

    15-12-2005 835.85

    14-12-2005 858.05

    13-12-2005 852.7

    12-12-2005 852.2

    09-12-2005 856

    08-12-2005 825.05

    07-12-2005 824.45

    06-12-2005 806.4

    05-12-2005 797.85

    02-12-2005 823.6

    01-12-2005 822.6

    30-11-2005 833.75

    29-11-2005 851.65

    28-11-2005 859.9525-11-2005 849.3

    24-11-2005 840.85

    23-11-2005 843.4

    22-11-2005 835.65

    21-11-2005 838.65

    18-11-2005 816.9

  • 8/7/2019 Business_Statistics_Project2_2010

    57/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    57

    17-11-2005 806.65

    16-11-2005 792.1

    15-11-2005 786.4

    14-11-2005 786.4

    11-11-2005 806.2

    10-11-2005 777.25

    09-11-2005 778.5

    08-11-2005 788.7

    07-11-2005 749.05

    04-11-2005 715.7

    03-11-2005 715.7

    02-11-2005 715.7

    01-11-2005 707.9

    31-10-2005 707.9

    28-10-2005 696.3

    27-10-2005 721.05

    26-10-2005 705.35

    25-10-2005 715.6

    24-10-2005 726.85

    21-10-2005 743.1

    20-10-2005 698.4

    19-10-2005 688.6

    18-10-2005 716.45

    17-10-2005 696

    14-10-2005 689.95

    13-10-2005 703.25

    12-10-2005 729.4

    11-10-2005 729.4

    10-10-2005 743.4

    07-10-2005 731.05

    06-10-2005 743.75

    05-10-2005 756.85

    04-10-2005 763.4

    03-10-2005 748.5530-09-2005 741.3

    29-09-2005 744.05

    28-09-2005 726.95

    27-09-2005 715.3

    26-09-2005 713.4

    23-09-2005 699.6

  • 8/7/2019 Business_Statistics_Project2_2010

    58/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    58

    22-09-2005 691.95

    21-09-2005 704.2

    20-09-2005 704.2

    19-09-2005 697.2

    16-09-2005 684.9

    15-09-2005 685.2

    14-09-2005 686.6

    13-09-2005 691.6

    12-09-2005 698.25

    09-09-2005 693.6

    08-09-2005 701.25

    07-09-2005 703.45

    06-09-2005 703.45

    05-09-2005 695

    02-09-2005 684.5

    01-09-2005 666.05

    31-08-2005 646.4

    30-08-2005 641.2

    29-08-2005 643.55

    26-08-2005 652.05

    25-08-2005 650.2

    24-08-2005 649.9

    23-08-2005 683.7

    22-08-2005 683.7

    19-08-2005 679.05

    18-08-2005 681.2

    17-08-2005 678.4

    16-08-2005 679.75

    15-08-2005 693.1

    12-08-2005 693.1

    11-08-2005 654

    10-08-2005 626.2

    09-08-2005 608.65

    08-08-2005 606.5505-08-2005 615

    04-08-2005 630.65

    03-08-2005 626.95

    02-08-2005 631.45

    01-08-2005 632.65

    29-07-2005 622.7

  • 8/7/2019 Business_Statistics_Project2_2010

    59/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    59

    28-07-2005 609.9

    27-07-2005 609.9

    26-07-2005 609.95

    25-07-2005 605.6

    22-07-2005 616.6

    21-07-2005 607.3

    20-07-2005 615

    19-07-2005 638.35

    18-07-2005 654.3

    15-07-2005 628.4

    14-07-2005 620.55

    13-07-2005 632.2

    12-07-2005 592.8

    11-07-2005 592.8

    08-07-2005 586.6

    07-07-2005 581.25

    06-07-2005 576.75

    05-07-2005 578.85

    04-07-2005 583.75

    01-07-2005 582.5

    30-06-2005 582.5

    29-06-2005 576.85

    28-06-2005 576.7

    27-06-2005 584.85

    24-06-2005 601.95

    23-06-2005 580.8

    22-06-2005 554.9

    21-06-2005 550.15

    20-06-2005 548.15

    17-06-2005 551.05

    16-06-2005 550.8

    15-06-2005 549.4

    14-06-2005 540.35

    13-06-2005 551.810-06-2005 551.8

    09-06-2005 555.6

    08-06-2005 557.3

    07-06-2005 555.25

    06-06-2005 552.3

    03-06-2005 557.9

  • 8/7/2019 Business_Statistics_Project2_2010

    60/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    60

    02-06-2005 557.9

    01-06-2005 560

    31-05-2005 552.9

    30-05-2005 569.35

    27-05-2005 594.4

    26-05-2005 594.4

    25-05-2005 578.75

    24-05-2005 568.5

    23-05-2005 571.1

    20-05-2005 567.95

    19-05-2005 560.65

    18-05-2005 550.1

    17-05-2005 550.1

    16-05-2005 552.05

    13-05-2005 546.35

    12-05-2005 552.05

    11-05-2005 551.2

    10-05-2005 546.9

    09-05-2005 550.5

    06-05-2005 540.55

    05-05-2005 539.4

    04-05-2005 528.8

    03-05-2005 513.3

    02-05-2005 515.2

    29-04-2005 503.65

    28-04-2005 521

    27-04-2005 501.8

    26-04-2005 504.55

    25-04-2005 507.5

    22-04-2005 506.5

    21-04-2005 515.65

    20-04-2005 515.1

    19-04-2005 486.45

    18-04-2005 501.115-04-2005 517.5

    14-04-2005 513.65

    13-04-2005 513.65

    12-04-2005 525.65

    11-04-2005 533.55

    08-04-2005 533.55

  • 8/7/2019 Business_Statistics_Project2_2010

    61/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    61

    07-04-2005 541.25

    06-04-2005 535.3

    05-04-2005 539.7

    04-04-2005 536.6

    01-04-2005 544.5

    31-03-2005 548

    30-03-2005 544.25

    29-03-2005 519.05

    28-03-2005 540.7

    25-03-2005 544.35

    24-03-2005 544.35

    23-03-2005 545.6

    22-03-2005 530.7

    21-03-2005 535.85

    18-03-2005 539.1

    17-03-2005 553.65

    16-03-2005 553.65

    15-03-2005 564

    14-03-2005 574.85

    11-03-2005 563.75

    10-03-2005 553.85

    09-03-2005 553.85

    08-03-2005 554.65

    07-03-2005 562.5

    04-03-2005 560.2

    03-03-2005 563.05

    02-03-2005 550.3

    01-03-2005 548.55

    28-02-2005 544.55

    25-02-2005 519.4

    24-02-2005 537.1

    23-02-2005 536.6

    22-02-2005 540

    21-02-2005 54218-02-2005 535.8

    17-02-2005 531.4

    16-02-2005 548.7

    15-02-2005 555.6

    14-02-2005 563.95

    11-02-2005 550.35

  • 8/7/2019 Business_Statistics_Project2_2010

    62/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    62

    10-02-2005 532.45

    09-02-2005 529.65

    08-02-2005 528.4

    07-02-2005 533.45

    04-02-2005 542.8

    03-02-2005 533.95

    02-02-2005 529.95

    01-02-2005 531.45

    31-01-2005 538.1

    28-01-2005 531.4

    27-01-2005 540

    26-01-2005 524.1

    25-01-2005 524.1

    24-01-2005 537

    21-01-2005 537

    20-01-2005 537

    19-01-2005 542.65

    18-01-2005 535.95

    17-01-2005 521.85

    14-01-2005 524.55

    13-01-2005 554.2

    12-01-2005 550.15

    11-01-2005 571.1

    10-01-2005 576.2

    07-01-2005 572.45

    06-01-2005 576.35

    05-01-2005 566

    04-01-2005 612

    03-01-2005 601.05

    31-12-2004 572.35

    30-12-2004 568.95

    29-12-2004 559.7

    28-12-2004 549

    27-12-2004 54924-12-2004 548.75

    23-12-2004 547.4

    22-12-2004 553.85

    21-12-2004 557.7

    20-12-2004 522.1

    17-12-2004 508.7

  • 8/7/2019 Business_Statistics_Project2_2010

    63/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    63

    16-12-2004 509.1

    15-12-2004 518.8

    14-12-2004 507.3

    13-12-2004 480.85

    10-12-2004 480.85

    09-12-2004 487.95

    08-12-2004 490.2

    07-12-2004 490.4

    06-12-2004 487.3

    03-12-2004 475.25

    02-12-2004 474.65

    01-12-2004 469.45

    30-11-2004 492.8

    29-11-2004 482.55

    26-11-2004 473

    25-11-2004 473

    24-11-2004 446.6

    23-11-2004 439.45

    22-11-2004 443.05

    19-11-2004 442.4

    18-11-2004 442.4

    17-11-2004 451.75

    16-11-2004 441.3

    15-11-2004 438.3

    12-11-2004 438.3

    11-11-2004 434.95

    10-11-2004 442.3

    09-11-2004 434

    08-11-2004 435.25

    05-11-2004 427.3

    04-11-2004 432.65

    03-11-2004 428.95

    02-11-2004 429.6

    01-11-2004 426.9529-10-2004 429.25

    28-10-2004 429.25

    27-10-2004 437.3

    26-10-2004 425.2

    25-10-2004 416.8

    22-10-2004 419.6

  • 8/7/2019 Business_Statistics_Project2_2010

    64/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    64

    21-10-2004 419.6

    20-10-2004 420.45

    19-10-2004 420.55

    18-10-2004 420.9

    15-10-2004 426.05

    14-10-2004 426.05

    13-10-2004 425.7

    12-10-2004 425.7

    11-10-2004 430.55

    08-10-2004 437.6

    07-10-2004 437.6

    06-10-2004 430.45

    05-10-2004 444.4

    04-10-2004 453.3

    01-10-2004 454.05

    30-09-2004 448.2

    29-09-2004 436.55

    28-09-2004 435.15

    27-09-2004 442.6

    24-09-2004 442.65

    23-09-2004 446.3

    22-09-2004 455.15

    21-09-2004 449.95

    20-09-2004 453

    17-09-2004 458.15

    16-09-2004 458.45

    15-09-2004 457

    14-09-2004 462.75

    13-09-2004 446.15

    10-09-2004 442

    09-09-2004 442

    08-09-2004 450.3

    07-09-2004 455.4

    06-09-2004 451.0503-09-2004 442.55

    02-09-2004 443.95

    01-09-2004 447.1

    31-08-2004 442.95

    30-08-2004 449.45

    27-08-2004 443.35

  • 8/7/2019 Business_Statistics_Project2_2010

    65/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    65

    26-08-2004 447.85

    25-08-2004 449.05

    24-08-2004 449.55

    23-08-2004 449.4

    20-08-2004 447.2

    19-08-2004 448.75

    18-08-2004 438.9

    17-08-2004 441.05

    16-08-2004 434.4

    13-08-2004 441.2

    12-08-2004 450.15

    11-08-2004 450.15

    10-08-2004 464.15

    09-08-2004 465.8

    06-08-2004 452

    05-08-2004 447.6

    04-08-2004 430.1

    03-08-2004 432.3

    02-08-2004 438.1

    30-07-2004 429.2

    29-07-2004 417.8

    28-07-2004 433.8

    27-07-2004 442.35

    26-07-2004 442.35

    23-07-2004 440.4

    22-07-2004 437.35

    21-07-2004 440.7

    20-07-2004 436.3

    19-07-2004 451.7

    16-07-2004 462.45

    15-07-2004 459.8

    14-07-2004 450.75

    13-07-2004 467.85

    12-07-2004 486.909-07-2004 501.5

    08-07-2004 491

    07-07-2004 520.95

    06-07-2004 528.4

    05-07-2004 516.15

    02-07-2004 511.25

  • 8/7/2019 Business_Statistics_Project2_2010

    66/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    66

    01-07-2004 504.1

    30-06-2004 506.75

    29-06-2004 507.75

    28-06-2004 489.3

    25-06-2004 492.75

    24-06-2004 489.55

    23-06-2004 470.1

    22-06-2004 474.85

    21-06-2004 482.15

    18-06-2004 472.5

    17-06-2004 472.9

    16-06-2004 476

    15-06-2004 482.25

    14-06-2004 474.4

    11-06-2004 474.6

    10-06-2004 473.25

    09-06-2004 479.2

    08-06-2004 481.35

    07-06-2004 469.55

    04-06-2004 478.65

    03-06-2004 469.85

    02-06-2004 478.45

    01-06-2004 462.1

    31-05-2004 445.85

    28-05-2004 450.25

    27-05-2004 488.7

    26-05-2004 476.95

    25-05-2004 481.6

    24-05-2004 474.15

    21-05-2004 458.9

    20-05-2004 449.6

    19-05-2004 441.45

    18-05-2004 433.3

    17-05-2004 408.214-05-2004 442.95

    13-05-2004 452

    12-05-2004 463.6

    11-05-2004 462.8

    10-05-2004 485.25

    07-05-2004 492

  • 8/7/2019 Business_Statistics_Project2_2010

    67/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    67

    06-05-2004 492.55

    05-05-2004 480.85

    04-05-2004 474.1

    03-05-2004 462.55

    30-04-2004 481.8

    29-04-2004 481.05

    28-04-2004 479.45

    27-04-2004 481.35

    26-04-2004 498.55

    23-04-2004 498.55

    22-04-2004 501

    21-04-2004 499.9

    20-04-2004 486.4

    19-04-2004 488.9

    16-04-2004 502.65

    15-04-2004 502.65

    14-04-2004 501.7

    13-04-2004 501.7

    12-04-2004 504.85

    09-04-2004 513.1

    08-04-2004 513.1

    07-04-2004 504.5

    06-04-2004 489.85

    05-04-2004 493.55

    02-04-2004 495.6

    01-04-2004 501.8

    31-03-2004 490.6

    30-03-2004 478.35

    29-03-2004 479.15

    26-03-2004 470.35

    25-03-2004 463.05

    24-03-2004 461.9

    23-03-2004 450.4

    22-03-2004 444.519-03-2004 453.75

    18-03-2004 453.45

    17-03-2004 467

    16-03-2004 478.35

    15-03-2004 450.25

    12-03-2004 475.1

  • 8/7/2019 Business_Statistics_Project2_2010

    68/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    68

    11-03-2004 472.75

    10-03-2004 496.15

    09-03-2004 530.95

    08-03-2004 539.5

    05-03-2004 533.5

    04-03-2004 520.1

    03-03-2004 524.15

    02-03-2004 516.95

    01-03-2004 516.95

    27-02-2004 492.55

    26-02-2004 499.8

    25-02-2004 499.85

    24-02-2004 513.5

    23-02-2004 485.1

    20-02-2004 511.6

    19-02-2004 491.15

    18-02-2004 504.05

    17-02-2004 498.3

    16-02-2004 504.3

    13-02-2004 501

    12-02-2004 505.6

    11-02-2004 483.15

    10-02-2004 480.3

    09-02-2004 483.1

    06-02-2004 463.9

    05-02-2004 463

    04-02-2004 460.75

    03-02-2004 438.85

    02-02-2004 452.1

    30-01-2004 452.1

    29-01-2004 448.05

    28-01-2004 459

    27-01-2004 464.4

    26-01-2004 455.223-01-2004 455.2

    22-01-2004 427.5

    21-01-2004 450.9

    20-01-2004 481.9

    19-01-2004 485.05

    16-01-2004 462.05

  • 8/7/2019 Business_Statistics_Project2_2010

    69/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    69

    15-01-2004 459.7

    14-01-2004 479.5

    13-01-2004 490.55

    12-01-2004 484.4

    09-01-2004 482.95

    08-01-2004 455.75

    07-01-2004 446.85

    06-01-2004 445.8

    05-01-2004 450.6

    02-01-2004 466

    01-01-2004 458.9

    31-12-2003 448.4

    30-12-2003 453.4

    29-12-2003 463.6

    26-12-2003 462.3

    25-12-2003 447.9

    24-12-2003 447.9

    23-12-2003 417.25

    22-12-2003 409.4

    19-12-2003 412.7

    18-12-2003 397.7

    17-12-2003 389.75

    16-12-2003 386.7

    15-12-2003 397.85

    12-12-2003 396.3

    11-12-2003 399.85

    10-12-2003 395.6

    09-12-2003 397.3

    08-12-2003 384.8

    05-12-2003 380.7

    04-12-2003 391.15

    03-12-2003 404

    02-12-2003 408.85

    01-12-2003 397.528-11-2003 374.55

    27-11-2003 374.55

    26-11-2003 378.95

    25-11-2003 378.95

    24-11-2003 372.85

    21-11-2003 373.55

  • 8/7/2019 Business_Statistics_Project2_2010

    70/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    70

    20-11-2003 381.25

    19-11-2003 376.95

    18-11-2003 384.25

    17-11-2003 394.1

    14-11-2003 385.75

    13-11-2003 385.75

    12-11-2003 383.35

    11-11-2003 369.6

    10-11-2003 370.25

    07-11-2003 361.95

    06-11-2003 372.85

    05-11-2003 366.4

    04-11-2003 368.7

    03-11-2003 370.1

    31-10-2003 353.1

    30-10-2003 323.6

    29-10-2003 303.9

    28-10-2003 303.15

    27-10-2003 318.1

    24-10-2003 310.2

    23-10-2003 310.2

    22-10-2003 315.55

    21-10-2003 322.1

    20-10-2003 329.25

    17-10-2003 329.7

    16-10-2003 331.05

    15-10-2003 338.85

    14-10-2003 335.05

    13-10-2003 333.55

    10-10-2003 322.45

    09-10-2003 324.7

    08-10-2003 324.05

    07-10-2003 325.05

    06-10-2003 330.4503-10-2003 324.1

    02-10-2003 310.35

    01-10-2003 310.35

    30-09-2003 308.65

    29-09-2003 295.75

    26-09-2003 294.45

  • 8/7/2019 Business_Statistics_Project2_2010

    71/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    71

    25-09-2003 286.4

    24-09-2003 298.35

    23-09-2003 286.95

    22-09-2003 280.4

    19-09-2003 281

    18-09-2003 270.95

    17-09-2003 280.55

    16-09-2003 285.3

    15-09-2003 278.6

    12-09-2003 284.25

    11-09-2003 287.4

    10-09-2003 291.2

    09-09-2003 283.6

    08-09-2003 284.6

    05-09-2003 287.4

    04-09-2003 285.65

    03-09-2003 282.8

    02-09-2003 290.35

    01-09-2003 292.55

    29-08-2003 294.3

    28-08-2003 293.3

    27-08-2003 295.95

    26-08-2003 291.05

    25-08-2003 275

    22-08-2003 278.8

    21-08-2003 269.05

    20-08-2003 265.2

    19-08-2003 266.45

    18-08-2003 269.25

    15-08-2003 267.7

    14-08-2003 267.7

    13-08-2003 274.45

    12-08-2003 276.4

    11-08-2003 271.3508-08-2003 272.05

    07-08-2003 269.65

    06-08-2003 268.1

    05-08-2003 269.9

    04-08-2003 270.5

    01-08-2003 273.15

  • 8/7/2019 Business_Statistics_Project2_2010

    72/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    72

    31-07-2003 266.9

    30-07-2003 251.5

    29-07-2003 248.05

    28-07-2003 246

    25-07-2003 241.85

    24-07-2003 237.6

    23-07-2003 239

    22-07-2003 239.55

    21-07-2003 245.55

    18-07-2003 246.2

    17-07-2003 242.25

    16-07-2003 239.05

    15-07-2003 263.4

    14-07-2003 259.7

    11-07-2003 257.5

    10-07-2003 256.85

    09-07-2003 254

    08-07-2003 256.7

    07-07-2003 256.25

    04-07-2003 257.35

    03-07-2003 254.6

    02-07-2003 253.45

    01-07-2003 251.3

    30-06-2003 253.8

    27-06-2003 253.1

    26-06-2003 251.05

    25-06-2003 245.55

    24-06-2003 245

    23-06-2003 240.2

    20-06-2003 245.65

    19-06-2003 246.4

    18-06-2003 246.35

    17-06-2003 251

    16-06-2003 241.0513-06-2003 251.7

    12-06-2003 245.6

    11-06-2003 240.15

    10-06-2003 237.55

    09-06-2003 236.95

    06-06-2003 233.9

  • 8/7/2019 Business_Statistics_Project2_2010

    73/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    73

    05-06-2003 234.2

    04-06-2003 228.7

    03-06-2003 229.5

    02-06-2003 223.25

    30-05-2003 213.55

    29-05-2003 221.2

    28-05-2003 221.8

    27-05-2003 222.15

    26-05-2003 219.05

    23-05-2003 220.8

    22-05-2003 222.8

    21-05-2003 233.65

    20-05-2003 236

    19-05-2003 229.4

    16-05-2003 228.45

    15-05-2003 219.55

    14-05-2003 219.6

    13-05-2003 214.15

    12-05-2003 206.05

    09-05-2003 205.4

    08-05-2003 209.65

    07-05-2003 213.3

    06-05-2003 209.7

    05-05-2003 205.45

    02-05-2003 205.45

    01-05-2003 203.4

    30-04-2003 203.4

    29-04-2003 203.4

    28-04-2003 196.9

    25-04-2003 195.7

    24-04-2003 187.95

    23-04-2003 188.05

    22-04-2003 183.35

    21-04-2003 183.218-04-2003 186.05

    17-04-2003 186.05

    16-04-2003 194.2

    15-04-2003 195.75

    14-04-2003 206

    11-04-2003 206

  • 8/7/2019 Business_Statistics_Project2_2010

    74/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    74

    10-04-2003 193

    09-04-2003 183.85

    08-04-2003 188.7

    07-04-2003 195.05

    04-04-2003 193.4

    03-04-2003 194.55

    02-04-2003 191.25

    01-04-2003 185.95

    31-03-2003 188.2

    28-03-2003 196.85

    27-03-2003 203.35

    26-03-2003 215.55

    25-03-2003 222.9

    24-03-2003 225.3

    21-03-2003 228.65

    20-03-2003 228.65

    19-03-2003 216.05

    18-03-2003 222

    17-03-2003 222

    14-03-2003 225.8

    13-03-2003 225.8

    12-03-2003 219.55

    11-03-2003 226.6

    10-03-2003 212.8

    07-03-2003 212.95

    06-03-2003 223.65

    05-03-2003 224.3

    04-03-2003 225.15

    03-03-2003 225

    28-02-2003 223

    27-02-2003 220.5

    26-02-2003 219.1

    25-02-2003 221

    24-02-2003 220.3521-02-2003 220.25

    20-02-2003 224.95

    19-02-2003 227.05

    18-02-2003 218.15

    17-02-2003 213.3

    14-02-2003 206.2

  • 8/7/2019 Business_Statistics_Project2_2010

    75/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    75

    13-02-2003 218.5

    12-02-2003 218.5

    11-02-2003 220.15

    10-02-2003 231.85

    07-02-2003 237.5

    06-02-2003 238

    05-02-2003 245.6

    04-02-2003 254.6

    03-02-2003 253

    31-01-2003 254.95

    30-01-2003 255.25

    29-01-2003 249.6

    28-01-2003 242.85

    27-01-2003 241.3

    24-01-2003 236.7

    23-01-2003 238.4

    22-01-2003 238.6

    21-01-2003 238.2

    20-01-2003 239.85

    17-01-2003 245.95

    16-01-2003 250

    15-01-2003 247.5

    14-01-2003 245.65

    13-01-2003 248.15

    10-01-2003 250.25

    09-01-2003 249.7

    08-01-2003 252.85

    07-01-2003 251.75

    06-01-2003 258.65

    03-01-2003 262

    02-01-2003 261.1

    01-01-2003 261.6

    31-12-2002 268.2

    30-12-2002 269.3527-12-2002 269.75

    26-12-2002 270.25

    25-12-2002 268.4

    24-12-2002 268.4

    23-12-2002 273.85

    20-12-2002 279.1

  • 8/7/2019 Business_Statistics_Project2_2010

    76/430

    Comparative Analysis of Automobile Sector and Telecom Sector using ANOVA

    76

    19-12-2002 281.4

    18-12