As per A.L. Bowley, Statistics is called as Science of counting and averages Science of counting and averages. As per Boddington, statistics is science of estimates and probabilities As per Wallis and Roberts statistics is As per Wallis and Roberts, statistics is regarded as a body of methods of decision making in the face of uncertainty making in the face of uncertainty .
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As per A.L. Bowley, Statistics is called asScience of counting and averagesScience of counting and averages.
As per Boddington, statistics is science ofestimates and probabilities
As per Wallis and Roberts statistics isAs per Wallis and Roberts, statistics isregarded as a body of methods of decisionmaking in the face of uncertaintymaking in the face of uncertainty.
As per Horace Secrist :: Statistics isd d th t f f t ff t dregarded as the aggregate of facts affected
to a marked extent by multiplicity of causes,i ll d ti t dnumerically expressed or estimated
according to a reasonable standard ofll t d i t tiaccuracy, collected in a systematic manner
for a predetermined purpose and placed inl ti t h threlation to each other.
A captain of a cricket team needs to knowA captain of a cricket team needs to knowhow many players in his team are batsmen,bowlers wicket keepers and all rounder ?bowlers, wicket-keepers and all rounder ?
A Head of a state, a head of a family needsyall information related to them which helpsthem to tackle the situations.
The information is expressed in numbers,which is called statistical datawhich is called statistical data
I) Ungrouped data (or) Individual items (or)Raw data
II) Grouped Data
a) Discrete frequency Distribution
b) Continuous Frequency Distributionb) Continuous Frequency Distribution
Marks obtained by 30 students in a test ofMarks obtained by 30 students in a test of Mathematics subject out of 50 marks is given below ::below ::
15 21 40 30 18 16 23 27 17 40
34 32 36 19 28 41 42 31 35 40
38 39 44 43 37 36 42 28 33 40
H d l ifi iHence needs classification
There are 150 families in a village. Number offamilies having no child, one child, two children etcis given belowNo. of Children No. of families (F)
00 78
01 2201 22
02 22
03 1603 16
04 04
05 0305 03
06 05
150
M kM k 00 1010 1010 2020 2020 3030 3030 4040 4040 5050 5050 6060Marks Marks ObtainedObtained
No. of No. of 1212 1818 2727 2020 1717 66studentsstudents
0-10, 10-20 etc are called class intervals and 12 is called0 10, 10 20 etc are called class intervals and 12 is calledfrequency.
A frequency is a number which tells how many students haveq y ytaken marks between 0 and 10. Hence in 0-10, 10 isexcluded in first class.
Class interval
The range of variables that canThe range of variables that can be divided into subgroups or g psub-rangers is called class intervals or classesintervals or classes.
WIDTH OF THE CI :: The difference betweenlower and upper class limits is called width of CIppClass frequency: The number of observationscorresponding to a particular class is calledp g pfrequency. i.e. it is a number which tells howmany observations fall in a particular classy pTypes Of Class IntervalsExclusive typeyp
If upper limit of first Class Interval = lower limitof second class interval then they are calledof second class interval then they are calledoverlapping class limits
Class Class IntervalsIntervals
Frequency Frequency
00--1010 22
1010 2020 331010--2020 332020--3030 55
Example:: If an observation is 10 then it falls in 2nd Class Intervals and not in 1st class intervals2 Class Intervals and not in 1 class intervals.
Class Class IntervalsIntervals
Frequency Frequency IntervalsIntervals
00--99 55
1010 1919 111010--1919 11
2020--2929 33
Upper Limit of 1st class interval ≠ Lower Limit of 2nd
class intervals
The following are marks scored by30 t d t i th ti t t30 students in mathematics test.Prepare a frequency distributiontable taking 5 as width of the class.
Arithmetic Mean is defined as the sum of all theArithmetic Mean is defined as the sum of all the observations divided by total number of observations
I i d d b b lIt is denoted by symbol xRaw data : (ungrouped data)
x = ∑x
n
X = Value taken by the variables
∑x = Summation of X∑x = Summation of X
n = Total number of observation
Student Student AA BB CC DD EE FF GG HHMarksMarks 6767 7676 8282 4444 6060 7171 5454 6666
i.e. The mean marks of 8 students of the class = 65
Calculation of mean becomesdifficult if the raw data consists oftoo many numbers It is better totoo many numbers. It is better togroup the raw data into discrete and
i i S hcontinuous series. So thatcalculation of mean becomessimpler.
X = ∑fxX = ∑fx
N
X = Value taken by the variable
X = MeanX = Mean
f = Frequency corresponding to X
N = ∑f (Total member of observation)
H i h (iH i h (i 5050 5252 5454 5555 5656Heights (in Heights (in inches)inches)
5050 5252 5454 5555 5656
No.of personsNo.of persons 22 22 33 22 11pp
Solutions :: Calculation of mean by direct methodHeightsHeights PersonsPersons fxfxgg
i.e. in the cumulative frequency column,th l th 25 i 42 ththe value more than 25 is 42. thecorresponding X value is 30.
M = 30 Marks
or
Median Marks is 30
Mode:Mode:Mode is defined as the value which is
t d i b f ti irepeated maximum number of times in a data. It may be denoted by the letter Zy y
RAW DATA
Marks Marks ScoredScored
1212 1515 2020 1010 3030 2020 1010 2020
Solution:
Here, 20 occurs three times and otherHere, 20 occurs three times and othernumbers do not occur so often.
Therefore, 20 is the mode
E l l l t di d dExample :: calculate mean, median and mode for the following ungrouped data
90 70 53 95 72 7090, 70, 53, 95, 72, 70
Mean = AM = average = 90 + 70 + 53 + 95 + 72 + 70Mean AM average 90 + 70 + 53 + 95 + 72 + 70
6
= 450
66
= 75
Median = 53, 70, 70, 72, 90, 92Arrange in ascending order
Mode :
Mode = 70 repeated score (crude mode)
( ) M d 3 di 2 M(or) Mode = 3 median - 2 Mean
= 3(71) - 2 (75)
= 63 (Real Mode)
EXAMPLE 2One foot ball team scored 1,3, 2, 6, 4,0,2, 5, 3, 3, 1, 2, 4, 6,3 2 1 4 3 5 3 1 goals in the matches if played in order3, 2, 1, 4, 3, 5, 3,1, goals in the matches if played in order.Prepare frequency distribution table and find mean, medianand made Values (x)Values (x) ff fxfx cfcf