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Impact of Entrepreneurship Development on the

socio-economic status of women and their families

Dr.R.Gopal and Rashmi. Gopinathan

Director-Dean, Sr.Lecturer

Padmashree.Dr.D.Y.Patil University, Department of BusinessManagement.

Introduction

Women form an important part of the labour force and the economic roleplayed by them cannot be isolated from the framework of development. The

role and degree of integration of women in economic development is anindicator of economic independence and higher social status of women.Emergence of entrepreneurship is considered to be closely linked with social,cultural, religious and psychological variables. These changes seem to havebecome acceptable norms in the context of women at work in India today,with increasing number of women participation in economic development.Women Entrepreneurship in India is a recent phenomenon, which has comeon the scene in the seventies but became more prominent in the eighties,especially in the latter half of the decade. In the eighties, the gender and developmentapproach (GAD) influenced by social feminism, post modern and post colonialtheorists, look into account the totality of womens lives, rejecting the public/ private

dichotomy which serves to devaluate the work of women at home. Focus onperspectives on development makes women the subjects rather than objects of development, change agents rather than welfare recipients. The GAD approach is tomove women from the margin to the centre (Hooks 1984) by women gaining a senseof control over their lives (empowerment)

Around 73 percent (Sethi 1994) of the women entrepreneurs, in India have launchedtheir enterprises in the eighties and this trend appears to continue in the nineties. Therecognition of entrepreneurship is a quick route to socio economic development byplanners, the declaration of the International Decade of Women (1975-85) and thesetting up of a separate ministry for women and child welfare in 1985 have given aspurt to women entrepreneurship (Sethi 1994).

Women make the second largest target group for identification of potentialentrepreneurs, being slightly less than 50 percent of the total population. There are99.4 million women workers in a labour force of 272.84 million in India. Majority of the women seek employment out of economic necessity, but of these a large number are unable to find employment. Their share in total employment (40%) is higher thantheir share in the labour force (33%) (Rathore and Chhabra, 1991). It is not alwayseasy for women to find employment compatible with their family responsibilities andhousehold chores. Thus many women are attracted to the idea of self employment inenterprises adjoining their premises, with flexible hours allowing them to take care of both home and business. The last two decades has seen not only a substantial increase


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in employment of women but the last decade has seen a prominent role played bywomen entrepreneurs in the process of economic development (Fig.1)

4

96

5

95

9

91

13

87

20

78

24

72

0

10

20

30

40

50

60

70

80

90

100

1980 1985 1990 1996 2000 2006

Women

Men

Source: The Economic Times Financial Daily, 2007

The data shows that the participation of women in entrepreneurship during the postliberalization period is encouraging since the preparation has increased from 4% in

1980 to 13% in 1996 to 24% in 2006. There is also gradual increase in the rate of participation in the economy during the post liberalization period. The average annualgrowth of women entrepreneurship during the last decade is quite encouragingconsidering the inadequate growth during the first three decades of post independenceperiod (Table .1.)

Average Annual Growth of Enterprises under Women

Year Percentage of increase

1971 -80 1.58

1981-1990 5.19

1991-1996 9.65

1997-2006 13.23

Source: The Business Line, Economic Daily 2007.

The concept of entrepreneurship among poor women is becoming a globalphenomenon today as poor women are increasingly turning to entrepreneurship as a

way of coping with poverty. Venturing into micro enterprises to generate income isincreasingly being adopted by poor women as a livelihood strategy. The studies by

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Bhatt, Pecera, Anderson and Barohona (1995) illustrated how poor women microentrepreneurs, have utilized their entrepreneurial skills to become economicallyindependent and provided economic support to the family through entrepreneurship.

The state of Maharashtra was selected as locale for the present study as it is

the second most populous and third largest state by area in India. It is also therichest state in India contributing to 15% of the countrys industrial outputand 13.2% of GDP. The state is also a combination of urban population 42%and 58% rural population. The study was conducted in the rural Maharashtra.

Objective

1. To study the change in economic status of women and their families throughentrepreneurship development.

2. To study the change in decision making ability and enterprise development.

3. To asses the impact of social status of woman and their families.

4. To study the impact of women entrepreneurship development on family withrespect to standard of living.

5. To make recommendations in order to have empowerment of womenespecially among disadvantage group.

Research Methodology

The study initiated by having an open conversation with theorganizational heads of MAVIM (Mahila Aartik Vikas Mahamandal). Thisorganization was chosen as it has its presence felt in major districts of Maharashtra and is a body from the governments side which helps to bring inentrepreneurship development in the districts of Maharashtra and workingexclusively for the upliftment of women. The primary survey was criticalcomponent of the study as it would yield crucial data on the impact of womenentrepreneurship on their families from women Entrepreneur, grass rootworkers and district officers. The instrument used for the study is aquestionnaire. The state of Maharashtra was selected as locale for the presentstudy by using purposive sampling as it is the second most populous and thirdlargest state by area in India. Considering that Maharashtra has 35 districtsand is divided into Western Maharashtra, Marathwada,Vidarbh, Konkan andNorthern Maharashtra. The study is conducted for all the regions of Maharashtra as mentioned above, but taking only 2 districts from each regionbased on judgmental sampling. The total number of women entrepreneurs is500 through proportionate sampling and the villages chosen were on the basisof judgemental sampling(.table of sample Annex-1) The responses observedfor each of the items in the questionnaire were scored and tabulated into amaster sheet. The statistical tools included simple percentage, chi square test,factor analysis,. Paired t test.

Analysis

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The objective of the study was to assess the impact of womenentrepreneurship on family with respect to standard of living. This alsoexamined the Respondents socio-economic status with a view to examinewhether their economic and social status has lead to empowerment of respondents. The process of empowerment is a state of mind, an attitude of

women entrepreneurs in defining, challenging and overcoming barriers, inincreasing their ability to shape their lives and their environment. To assessthe empowerment of women after venturing into entrepreneurship the changein economic and social status. The questionnaire was designed to collect datafrom respondents with regard to their followings. Income, assets, Debts,savings and consumption patterns, both before and after they had venture intoentrepreneurship. After the data was collected, simple frequencies werecalculated. Based on the frequencies, values were calculated for each of thecomponents and then recorded. All positive values were recorded as 2, that isincrease, all negative values as 1 decrease and all zero value as nochange. Then the frequencies and percentages for the recorded values werecomputed to measure the change.

1. Change in Economic Status:The indicators used for assessing the change in the economic status of therespondents were occupation, monthly debt status, change in the expenditurepatterns in terms of education of children, food, household expenses andhealth.

1.a. Occupation:.1.a. The majority of the respondents (about 62%) were housewives and about(38%) were employed as daily wage workers before venturing intoentrepreneurship. The observations are shown in Table 1.a.

Table 1.a. Occupation:

Previous Occupation F (%)

Employed (Daily wage worker) 190 (38%)

Housewife 310 (62%)

Total 500 (100%)

It was reported by the respondents that MAVIM Mahila Artik VikasMahamangal and various other financial organizations had provided microfinance help, thereby economically empowering the respondents to start their business. The respondents were further supported by the organizationsthrough training for developing their entrepreneurial skills, facilitating theprocess of credit availability information and guidance, counseling and followup. A majority of the entrepreneurs went for micro enterprises as they weremore attractive to respondents because of low barriers to entry and flexiblenature of work, which made it easy to combine gainful employment with

domestic responsibilities.

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1.b. Monthly IncomeIncome measures the financial stability of a family. It also reveals thepurchasing power of the family to take care of basic household expenses,education of children and the like. It was found that the monthly income of the respondents had changed after they started their business.

Table 1. (b)Impact of Entrepreneurship on Income

Change in income No. of Respondents Percentage (%)

Increase 408 81.6%

Decrease 64 12.8%

No change 28 5.6%

Total 500 100%

The data in the table .1 (b) reveals that (82%) of the respondents reported an increasein the monthly income, around (13%) reported decrease and (6%) reported no changein income. The quantum change in income was also calculated on Table .1. (c).

Table.1. (c) : Change in the Monthly Income of Respondents

Monthly Income Change in Income level % changeincrease/DecreaseBefore After

Upto 2000 93.6% 6.4% - 87%

Rs. 2001 Rs.3000 69.6% 30.4% -39.0%

Rs. 3001 Rs.5000 8.6% 48.8% + 40.0%

Rs. 5000 & above 0.8% 13.6% + 12.8%

The data show that majority of the respondents (about 94%) had a monthlyincome upto Rs. 2000, followed by (70%) who had an income between

Rs.2001 to Rs.3000, (9%) had an income between Rs. 3001 to Rs.5000 and avery negligible percentage earned (0.8%) Rs. 5000 and above before theystarted the business activity.

The data further indicated that starting business had made an impact on thefinancial situation with the percentage of respondents who were earningbetween Rs. 2001 Rs. 3000 decreasing by (39%) and a correspondingincrease in the percentage of the respondents earning between Rs. 3001 Rs.5000 by (40%) and (13%) of the respondents also moved into the higher earning category of Rs. 5000 and above. This improvement in the financialcondition empowered the respondents to take decisions independently or jointly regarding the expenditure pattern of the household food, childreneducation. They also gained freedom to a greater extent to do what they

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wanted to do. The financial independence also helped the respondents toraise their standards of living. The data when further analysed revealedsignificant p value (Table 1. (d). indicating that venturing intoentrepreneurship had a positive influence on the monthly income.

Paired t-Test

Paired Differences

t df Sig. (2-tailed)Mean

Std.Deviation

Std. ErrorMean

95% ConfidenceInterval of theDifference

Lower Upper

Pair 1 VAR00001 -VAR00002 -5.82800 3574.16358 159.84145 -6142.04520

-5513.95480

-36.461 499 .000

.2.1 Change in the Decision making ability and EnterpriseDevelopment.

Entrepreneurs have to make decisions and this decision making capacitycomes from years of experience of being exposed to making necessarydecision, in situations both at work and home. The data in the table.2.2. showsthe type of decision makers who took decisions regarding the spendingpatterns before and after respondents started their business activities.

Table .2.1 Type of decision maker and decision on spending.

Type of DecisionMaker

Decision on spending Change Increase/Decrease

Before After

Spouse 385 (77%) 102 (20.4%) - 56.6%

Self 50 (10%) 317 (63.4%) + 53.4%

Joint 55 (11%) 72 (14.4%) + 3.4%

Family members 10 (2%) 9 (1.8%) Negligible change

The data in the table reveal that most of the decisions were made by thespouses (77%) before the respondents started the business which was reducedto (20.4%) which decreased by (56.6%). The most important part in thetransition from spouse to self, where the self decisions were (10%) whichincreased to (63.4%).The involvement of the respondent and her spouse alsoincreased from (11%) to (14.4%) an increase by (3.4%). This implies that onbecoming entrepreneurs they were exposed to making necessary decisions inincreasingly complex situations which enhanced their self-confidence to takeindependent decisions. The data revealed that with monetary returns frombusiness the respondents experienced a change in decision making.

.2.3. Asset Formation: The value of assets possessed by a family is animportant indicator of a secure condition of the family. The assets in thepresent study have been categorized in terms of fixed assets like house,jewellery, other household gadgets and savings. It was found that in case of

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(66%) of respondents, assets (in terms of value) had increased while (32%)there was no substantial change and very negligible percent decrease (1.6%).

Table.2.3: Impact of entrepreneurship development on Asset Formation

Change in Asset No. of Respondents Percentage

Increase 330 (66%)

Decrease 10 (1.6%)

No change 160 (32%)

Total 500 100%

The Respondents reported that they invested in buying jewellery for their daughters, in household gadgets like mixer grinder refrigerators and gasstoves. They further shared that they had started saving and had bank accountin their name. They did not only spend for themselves but a lot for their family. All these indicated a positive impact on the lives of the family of theRespondents.

.2.4. Debt Status: It was seen that another parameter to measure thestandard of living is the debt status of the family. The amount which thefamily could repay, has there been change in the debt status.

Table.2.4. : Debt Status

Change in Debt Status No. of Respondents Percentage

Increase 65 13%

Decrease 420 84%

No change 15 3%

Total 500 100%

The data as per table 8.2.4 the debt status as it was found was that it decreasedby (84%), (13%) respondents stated that it increased and (3%) stated that therewas no change. The increase respondents mentioned that the debt hasincreased as there was certain cases with spouses meeting with accident or daughters delivery etc. The respondents during the discussion also mentionedthat some of the respondents with the entrepreneurial activity profit did not goin for debt payment but reinvested in business. The entrepreneurial activitydid change the debt status for the respondent and their families which shows apositive impact.

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3. Change in Social Status:To assess the impact on the social status the following indicators were usedcontrol over earnings with regard to priority areas of spending and change inlifestyle with increase in the power of earning.

3.1. Individuals Control Over Earnings: As per discussions the respondentsrevealed that there was a drastic change in the status of control over earningafter they entering the entrepreneurial activity. The table below 8.2.5.1. givesthe details of the respondents responses.

Table3.1. : Individuals Control Over Earnings

Categories Control of Earnings

Yes No

Frequency 390 110

Percentage (78%) (22%)

The data on control over earning revealed that majority of the respondents(78%) had control over the earnings from the business with certain priorityareas for expenditure. During the discussion with the respondents they alsomentioned the priority areas of spending of respondents related to householdexpenses, where education of children by being able to buy milk, fruits, egg,chicken on regular basis and their own health. Based on different areas of spending the respondents responded (97%) spend part of their earnings likebuying monthly ration and clearing previous debts, (52%) spend on theeducation of their children and (21%) responded on meat, fish, and milk regularly for their children. The least priority was their own health.

3.2. Change in Life Style:The change in lifestyle was defined as the change in the purchasing power of the respondents ability to purchase goods and services for their families. Itwas observed as per the data collected that (71%) of the respondents reportedthat there was changes in their lifestyle. The data further revealed that around(72%) of the respondents had purchased goods for house like gas stove,refrigerator, mixer, grinder, television etc. About (37%) of them startedsavings in co-operative banks and Bank of India, State Bank of India etc. and(24%) disclosed that they were now able to buy clothes during the festivalseasons like Ganesh Chaturthi, Navaratri and Dipawali. Thus the respondentsfelt more responsible towards their families and were able and determined toimprove their financial situation and facilities at home

.

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4. Impact of Women Entrepreneurship Development on Familywith respect to Standard of Living :

The impact of women Entrepreneurship was further analyzed with the number of years of involvement of the respondents in business. The analysis was done

through discriminate analysis. Based on time duration, two groups wereformed one group who were involved in business for less than 2 years and theother group for more than 2 years. F test was used for checking thesignificance of variation in standard deviation.

The study of 500 respondents was undertaken to determine the correlates of thestandard of living of the family on the following characteristics. The predictor variables are consumption of food, house assets, status of house, childrenseducation, health issues, savings created ,literacy rate, social status, livelihood assets,psychological benefit. The dependant variable was the respondents involved inentrepreneurship, involvement for less than two years and more than two years of which two groups were identified. Respondents who reported their involvement inentrepreneurship less than 2 years classified as group 1 and those with more than 2years are classified as group 2.In testing for significance in the study noted that the Wilks Lamda valueassociated with the function is .439 which transforms to chi square of 405.947 with 11 degrees of freedom. This is significance beyond the 0.05level. The significance of the unvariable F Ratio indicates that when thepredicators are considered individually consumption of food, house assets,savings created, livelihood assets significantly differentiates who belong fromgroup 2. The Eigen value associated with function is 1.280 a (As per Table Annex.-) and the canonical correlation associated with function is 0.749.Hence the null hypothesis is rejected. Also with discussions with therespondents and previous data analysed, most of the respondents within ashort span of time brought about drastic change in their ownership as well asin the standard of living of the family. Kaccha to Paccka house, consumptionof nutritional food, and increase in assets such as cupboard, television, gasstove, fan, jewellery, livelihood assets etc. Thus the null hypothesis beingrejected, it was evident that involvement of women in entrepreneurship doesplay a significant role in standard of living of family.

Findings

1. The women entrepreneurs when enter into entrepreneurship have kachhahouse. House made of mud with a low entry and just with one room, noelectricity and no demarcating space for cooking with cow dung floors. Therespondents who have been in the entrepreneurship process for more than twoyears have brought remarkable change in the type of house. Most of therespondents who had their venture for 2 years, had pucca house made of cement. They had drawn electricity line and few of them even had brought intap connections. One thing very peculiar observed was some of them build atotally new house and kept the old house as a monument to keep marketingtheir journey and show the children and family the beginning.

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2. Consumption of Food : The other variable which was studied showed thatmajor lot of families who had only one income earner (i.e. women not beinginvolved as income earner) had basic diet as Dal, roti/ chappati/ bhakti and onesabji (may or may not be). Through discussions and analysis, the findingsrevealed that when the women enter into entrepreneurship the consumption

pattern of the house also changes. The women who have been earning moneyover two years responded that they do consume fish, egg and chicken atleastonce in a week. Some of them also responded that they did bring chickentwice a week. In regions of Konkan it was responded that they would bringcostly fish such as silver pomfert and black pomfret for the family especiallyfor the children. This also reflects the nutrition level for the family such asintake of protein, calcium, magnesium etc. Healthy living is brought throughthe process of women becoming income earners through entrepreneurship.

3.. House assets : As the respondents during the interview responded that many of them who have been involved in entrepreneurship process for over two yearshave brought cupboard, gas, table fan, cooker and other utensils, bed, somehave even gone to the extend of purchasing computer for their children. Themost purchased item for group 1 and group 2 was jewellery, fan, gas. In caseof women who have been in the business less than two years are happy thatthey could atleast purchase jewellery and have a shift from chulla to gas.Women involved over two years have also build bathrooms.

4. Savings : the women who have involved in entrepreneurship for less than twoyears have their SHG savings and house assets more. Most of them rather thanfocusing on savings of self have been focusing on sustaining their business byrolling their earnings back into the business. The people who have involvedthemselves in the entrepreneurship have generated self savings throughsavings account in bank on their name or children name. Most of them havealso invested money in post office savings and taken LIC policy. But it hasalsobeen found that those who have focused only on expansion of business andwhere the husbands involvement in business and decision making is totallycontrolled by husband the savings on the womens name is least. In areas suchas Gadchiroli they do not believe in savings but living life each other.

5. Livelihood Assets : It was observed and analyzed that most of the women didhave an attachment towards purchase of livelihood assets such as goat, sheep,

cow, pig etc. The only difference is in the responses attained from differentgeographical regions. In regions such as Gadchiroli people invested more inpig where as regions such as Konkan belt invested in cow and Nasik andAhmednagar invested in goat and sheep. Those who have responded and havebeen there in business over two years mentioned that they had began with onegoat and today have fifteen to twenty goats. Thos who have just recentlyentered have only one goat or nil livelihood assets.

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Conclusion

The study brought to light that most of the respondents have brought a change in their financial positions after starting the business which has also brought about a change in

the standard of living of the family. This has finally brought about a positive self esteem in the women entrepreneurs. Thus proving that there has been empowermentof women entrepreneurs through entrepreneurship development which has brought apositive impact on the lives of the family and improvement in the community andsociety at large.

Suggestions and recommendations

1. Requirement of Proactive Role of Government and Non-GovernmentOrganizations/ Institutions.

2. Training Programme for women Entrepreneurs should be more specific andpractical oriented:

a. Technical Modulesb. Support Modulesc. Social and Health Modules.

The above modules if would be incorporated there would be a drastic change in thelife style of women and their families in the rural Maharashtra as many of the womenlook forth for external support to bring a change.

Bibliography

Chandra, V.A.S. & Kajipet, D. 1988; Women Entrepreneurship in India: ARetrospect and Prospect In Lakshmi, C.S. (ed) Development of WomenEntrepreneurship in India. Discovery Publishing House, New Delhi

Charumathi, B. 1998; Women Entrepreneurs Challenges and Prospects In LakshmiC.S. (ed) Development of Women Entrepreneurship in India. Discovering PublishingHouse, New Delhi.

Chandra, S.K. 1991; Development of Women Entrepreneurship in India: A Study of Public Policies and Programmes. Mittal Publications, New Delhi.

Chandralekha, K. Kalyani, and Lovoice D. 1998; Micro enterprise Management byWomen in India. In Kanungo, R (ed) Entrepreneurship and Innovation SagePublications, New Delhi

Das, B.B.L. 1998; Requirements of Women Entrepreneurship Development in Indiawith Special reference to Bihar In Lakshmi, C.S. (ed) Development of WomenEntrepreneurship in India. Discovery Publication House, New Delhi

Dhillion, P. Kaur 1996;Women Entrepreneurs Problems and Prospects. BlazePublishers and Distributors (P) Ltd., New Delhi.

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Ghosh, R.: Gupta M and Nina D.S. Women and Entrepreneurship in India InKanungo, R.N. (ed.) Entrepreneurship and Innovation: Models for Development, SagePublications, New Delhi.

Iyer, L. 2007; Women Entrepreneurs -Challenges and Strategies Friedrick E.BertStifting New Delhi.

Jyothi, V. & Prasad, G.2009; A Profile of Potential Rural Women Entrepreneurs.SEDME Vol. XX(1).

Koshy and Joseph 2000; Women Entrepreneurs at the Micro level: Someobservations and thoughts, Productivity Vol. 38, No.4 January March

Lakshmi, C.S. (ed) Development of Women Entrepreneurship in India. DiscoveryPublishing House, New Delhi

Sethi, J. 1994; Women Entrepreneurship in India: A brief comment SEDME, Vol.XXI (4) December.

Shah, Hina 1987; Fostering Women Entrepreneurship: A Study DistinctiveFeatures. Research Report Serial 3, NIESBUD, New Delhi

Annex-1

The following table gives details of sample size throughout 10 districts of Maharashtra.

Sr.No. District

No. of Villages (SV) No. of WomenEntrepreneur(s)

PopulationSampleselected Population

Sampleselected

1. RATNAGIRI (187) 4 2572 17

2. SINDHUDURG (176) 6 3830 25

3. PUNE (201) 10 7694 50

4. KOLHAPUR (137) 5 2693 18

5. LATUR (242) 8 8759 57

6. OSMANABAD (154) 8 5816 38

7. GADCHIROLI (451) 8 13076 858. BHANDARA (355) 6 12355 80

9. NASIK (326) 8 4021 26

10. AHMEDNAGAR (206) 10 15928 104

TOTAL 500

Source: Mahila Arthik Vikas Mahamandal.Consolidated data of all districts. (Annex. II)

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Annex -2LIST OF ACTIVITIES UNDERTAKEN BY WOMEN

ENTREPRENEURS

1. Garment Shop2. Vegetable Shop3. Kirana Shop4. Sale of Tiffins5. Sarees, Dress Material and cutlery shop.6. Xerox and computer Typing.7. Tailoring Shop.8. Fur Toys Manufacturing.9. Stationery shoop.10. Papad unit

11. Saree Fall beeding and embroidery.12. Beauty Parlour.13. Cycle renting and repairing.14. Distribution and Preparing Agarbatti.15. Hosiery Shop.16. Shoes and Bags manufacturing.17. STD/PCO booth.18. Photo studio.19. Bakery Shop.20. Cosmetic shop.21. Cigarette and Chocolate stall.22. Grinding shop.23. Soaked lentils.24. Dry fish25. Flower shop.26. Vada Pav Shop.27. Bangles28. Fish29. Milk stalls30. Maternity pad31. Woolen garments.32. Block printing.33. Pepsi Cola Manufacturing34. Sanitary Napkins35. Matts36. Bamboo brooms37. Honey unit38. Liquor unit39. Cashew unit40. Perfume unit etc.

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8.3. TableAnalysis Case Processing Summary

Unweighted Cases N Percent

Valid 500 100.0

Excluded Missing or out-of-range groupcodes 0 .0

At least one missingdiscriminating variable 0 .0

Both missing or out-of-rangegroup codes and at least onemissing discriminating variable

0 .0

Total 0 .0Total 500 100.0

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Group Statistics

VAR00011 Mean Std. Deviation

Valid N (listwise)

Unweighted Weighted

1 VAR00001 5.0398 1.49077 251 251.000

VAR00002 4.0120 1.66969 251 251.000

VAR00003 2.8606 1.86989 251 251.000

VAR00004 4.0359 1.60334 251 251.000

VAR00005 3.1992 1.88047 251 251.000

VAR00006 3.7131 1.73130 251 251.000

VAR00007 3.0717 1.90022 251 251.000

VAR00008 3.9203 1.76907 251 251.000

VAR00009 3.9124 1.73444 251 251.000

VAR00010 3.9522 1.58925 251 251.000VAR00012 1.9402 1.66386 251 251.000

2 VAR00001 5.0843 1.55961 249 249.000

VAR00002 4.0482 1.70320 249 249.000

VAR00003 5.4940 4.60025 249 249.000

VAR00004 4.1406 1.65598 249 249.000

VAR00005 4.6867 1.94228 249 249.000

VAR00006 4.5743 1.99685 249 249.000

VAR00007 4.9357 1.97665 249 249.000VAR00008 4.0602 1.61407 249 249.000

VAR00009 3.9237 1.63819 249 249.000

VAR00010 3.7751 1.62318 249 249.000

VAR00012 6.3414 4.43592 249 249.000

Total VAR00001 5.0620 1.52407 500 500.000

VAR00002 4.0300 1.68487 500 500.000

VAR00003 4.1720 3.74252 500 500.000

VAR00004 4.0880 1.62898 500 500.000

VAR00005 3.9400 2.04959 500 500.000

VAR00006 4.1420 1.91551 500 500.000

VAR00007 4.0000 2.14971 500 500.000

VAR00008 3.9900 1.69341 500 500.000

VAR00009 3.9180 1.68551 500 500.000

VAR00010 3.8640 1.60707 500 500.000

VAR00012 4.1320 4.00233 500 500.000

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Tests of Equality of Group Means

Wilks' Lambda F df1 df2 Sig.

VAR00001 1.000 .106 1 498 .744VAR00002 1.000 .058 1 498 .810

VAR00003 .876 70.510 1 498 .000VAR00004 .999 .516 1 498 .473VAR00005 .868 75.700 1 498 .000VAR00006 .949 26.557 1 498 .000VAR00007 .812 115.560 1 498 .000VAR00008 .998 .853 1 498 .356VAR00009 1.000 .006 1 498 .940VAR00010 .997 1.519 1 498 .218VAR00012 .697 216.392 1 498 .000

Analysis 1

Box's Test of Equality of Covariance Matrices

Log Determinants

VAR00011 Rank Log Determinant

1 11 3.1152 11 8.659Pooled within-groups 11 7.291

The ranks and natural logarithms of determinants printed are those of the groupcovariance matrices.

Test Results

Box's M 704.714F Approx. 10.432

Df1 66

Df2 7.907E5Sig. .000

Tests null hypothesis of equal population covariance matrices.

Summary of Canonical Discriminant Functions

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Eigenvalues

Function Eigenvalue % of Variance Cumulative %Canonical

Correlation

1 1.280 a 100.0 100.0 .749

a. First 1 canonical discriminant functions were used in the analysis.Wilks' Lambda

Test of Function(s) Wilks' Lambda Chi-square df Sig.

1 .439 405.947 11 .000

Standardized Canonical Discriminant Function Coefficients

Function1

VAR00001 -.039VAR00002 -.098VAR00003 -1.780VAR00004 .248VAR00005 -.072VAR00006 -.048VAR00007 1.029

VAR00008 .093VAR00009 -.080VAR00010 -.413VAR00012 1.990

Structure Matrix

Function1

VAR00012 .583VAR00007 .426

VAR00005 .345VAR00003 .333VAR00006 .204VAR00010 -.049VAR00008 .037VAR00004 .028VAR00001 .013VAR00002 .010VAR00009 .003

Pooled within-groups correlations between discriminating variables and

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Eigenvalues


Correlation

1 1.280 a 100.0 100.0 .749



1 .439 405.947 11 .000


Function1


VAR00008 .093VAR00009 -.080VAR00010 -.413VAR00012 1.990

Structure Matrix

Function1

VAR00012 .583VAR00007 .426



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Eigenvalues


Correlation

1 1.280 a 100.0 100.0 .749



1 .439 405.947 11 .000


Function1


VAR00008 .093VAR00009 -.080VAR00010 -.413VAR00012 1.990

Structure Matrix

Function1

VAR00012 .583VAR00007 .426



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Eigenvalues


Correlation

1 1.280 a 100.0 100.0 .749



1 .439 405.947 11 .000


Function1


VAR00008 .093VAR00009 -.080VAR00010 -.413VAR00012 1.990

Structure Matrix

Function1

VAR00012 .583VAR00007 .426



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Eigenvalues


Correlation

1 1.280 a 100.0 100.0 .749



1 .439 405.947 11 .000


Function1


VAR00008 .093VAR00009 -.080VAR00010 -.413VAR00012 1.990

Structure Matrix

Function1

VAR00012 .583VAR00007 .426



21


22/23

Functions at Group Centroids

VAR00011

Function

1

1 -1.1252 1.134

Unstandardized canonical discriminant functions evaluated at group means

Classification Statistics

Prior Probabilities for Groups

VAR00011 Prior

Cases Used in Analysis

Unweighted Weighted

1 .500 251 251.0002 .500 249 249.000

Total 1.000 500 500.000

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Classification Function Coefficients

VAR000111 2

VAR00001 2.166 2.108

VAR00002 .828 .697VAR00003 -.172 -1.319VAR00004 .655 .999VAR00005 .318 .233VAR00006 .654 .596VAR00007 -.240 .959VAR00008 .492 .616VAR00009 1.399 1.293VAR00010 .475 -.106VAR00012 .123 1.466(Constant) -15.001 -18.421

Fisher's linear discriminant functions

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