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Prof Anil Mishra Krupajal Management Studies Bhubaneswar-2
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CORRELATION CORRELATION ANALYSISANALYSIS
It is a statistical measure It is a statistical measure which shows relationship which shows relationship
between two or more variable between two or more variable moving in the same or in moving in the same or in
opposite directionopposite direction
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Visual Displays and Visual Displays and Correlation AnalysisCorrelation Analysis
• The The sample correlation coefficientsample correlation coefficient ( (rr) ) measures the degree of linearity in the measures the degree of linearity in the relationship between relationship between XX and and YY..
-1 -1 << rr << +1 +1
• rr = 0 indicates no linear relationship = 0 indicates no linear relationship
• In Excel, use =CORREL(array1,array2), In Excel, use =CORREL(array1,array2), where array1 is the range for where array1 is the range for XX and array2 is and array2 is the range for the range for YY..
•Correlation AnalysisCorrelation Analysis
Strong negative relationshipStrong negative relationship Strong positive relationshipStrong positive relationship
Types of correlationTypes of correlation
correlation
positive& negative
Simple ,multiple & partial
Linear & non-linear
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Methods of correlationMethods of correlation
• Scatter diagramScatter diagram
• Product moment or covarianceProduct moment or covariance
• Rank correlationRank correlation
• Concurrent deviationConcurrent deviation
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Scatter diagramScatter diagram
• Perfectly +vePerfectly +ve
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Less-degree +veLess-degree +ve
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Weak Positive Weak Positive CorrelationCorrelation
High degree +veHigh degree +ve
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Strong Positive Strong Positive CorrelationCorrelation
Perfectly -vePerfectly -ve
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High degree -veHigh degree -ve
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Strong Negative CorrelationStrong Negative Correlation
Less degree -veLess degree -ve
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Weak Negative Weak Negative CorrelationCorrelation
Zero degree Zero degree
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Karl Pearson correlation Karl Pearson correlation coefficientcoefficient
22.
.
.
),cov(
yx
yxr
yxr
yx
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WhereWhere
YYy
and
XXx
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problem
From the following data find the coefficient of correlation by Karl Pearson method
X:6 2 10 4 8Y:9 11 5 8 7
Sol.
X Y X-6 Y-8
6 9 0 1 0 1 0
2 11 -4 3 16 9 -12
10 5 4 -3 16 9 -12
8 8 -2 0 4 0 0
4 7 2 -1 4 1 -2
30 40 0 0 40 20 -26
2x 2y yx.
Sol.cont.
92.0800
26
20.40
26
.
.
85
40
65
30
22
yx
yxr
N
YY
N
XX
Direct methodDirect method
2222 ..
..
YYNXXN
YXXYNr
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Short-cut methodShort-cut method
2222 .
..
yyxx
yxyx
ddNddN
ddddN
r
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WhereWhere
meanassumeA
AYd
AXd
y
x
&
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Product moment methodProduct moment method
2
2
.
x
xyb
y
xyb
where
bbr
yx
xy
yxxy
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spearman’s Rank correlationspearman’s Rank correlation
yofrankR
XofrankR
RRD
where
NN
DR
y
x
yx
..
..
)1(
61
2
2
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problem
Calculate spearman’s rank correlation coefficient between advt.cost & sales from the following data
Advt.cost :39 65 62 90 82 75 25 98 36 78
Sales(lakhs): 47 53 58 86 62 68 60 91 51 84
Sol.X Y R-x R-y D
39 47 8 10 -2 4
65 53 6 8 -2 4
62 58 7 7 0 0
90 86 2 2 0 0
82 62 3 5 -2 4
75 68 5 4 1 1
25 60 10 6 4 16
98 91 1 1 0 0
36 51 9 9 0 0
78 84 4 3 1 1
30
2D
Sol.cont.
82.011
911
21
1010
30.61
61
3
3
2
R
R
R
NN
DR
In case of equal rankIn case of equal rank
itemsrepeatedofnom
where
NN
mmmmDR
.
1
........121
121
61
2
332
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problemA psychologist wanted to compare two
methods A & B of teaching. He selected a random sample of 22 students. He grouped them into 11 pairs so that the students in a pair have approximately equal scores in an intelligence test. In each pair one student was taught by method A and the other by method B and examined after the course. The marks obtained by them as follows
Pair:1 2 3 4 5 6 7 8 9 10 11A: 24 29 19 14 30 19 27 30 20 28 11B: 37 35 16 26 23 27 19 20 16 11 21
Sol.A B R-A R-B D
24 37 6 1 5 25
29 35 3 2 1 1
19 16 8.5 9.5 -1 1
14 26 10 4 6 36
30 23 1.5 5 -3.5 12.25
19 27 8.5 3 5.5 30.25
27 19 5 8 -3 9
30 20 1.5 7 -5.5 30.25
20 16 7 9.5 -2.5 6.25
28 11 4 11 -7 49
11 21 11 6 5 25
225
2D
Sol.cont.
0225.0
11211112
14212
14212
142D6
-1R
twicerepeated is
series16 Bin and twicerepeated are 30& 19 items theseriesA in
2
R
Properties of correlation Properties of correlation coefficientcoefficient
• r always lies between +1 & -1r always lies between +1 & -1i.e. -1<r<+1 i.e. -1<r<+1 • Two independent variables are Two independent variables are
uncorrelated but converse is not true uncorrelated but converse is not true • r is independent of change in origin and r is independent of change in origin and
scalescale• r is the G.M. of two regression r is the G.M. of two regression
coefficientscoefficients• r is symmetricalr is symmetrical
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Probable errorProbable error
n
rrPE
or
rSErPEn
rrSE
2
2
16745.0
6745.0
1
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The coefficient of determinationIt is the primary way we can measure the
extent or strength of the association that exists between two variables x & y . Because we have used a sample of points to develop regression lines .
It is denoted by 2r
Thank youThank you
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