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Correlation
Calculate Karl Pearson’s correlation co-efficient bv the assumed mean method.
|
X |
14 |
15 |
18 |
20 |
25 |
30 |
|
Y |
40 |
45 |
65 |
28 |
30 |
40 |
Calculate of Karl Pearson’s correlation co-efficient.
|
X |
Y |
dX |
dY |
dXdY |
dX2 |
dY2 |
|
14 |
40 |
–6 |
–5 |
30 |
36 |
25 |
|
15 |
45 |
–5 |
0 |
0 |
25 |
0 |
|
18 |
65 |
–2 |
20 |
–40 |
4 |
400 |
|
20 |
28 |
0 |
–17 |
0 |
0 |
289 |
|
25 |
30 |
5 |
–15 |
–75 |
25 |
225 |
|
30 |
40 |
10 |
–5 |
–50 |
100 |
25 |
|
N= 6 |
IΣdX = 2 |
Σ dY = 22 |
ΣdXdY = –13.5 |
Σ dX2 = 190 |
Σ dY2 = 964 |
A.M. of X series =20 A.M. of Y series = 45
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If rxy = 0 the variable X and Y are:
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If precisely measured data are available the simple correlation coefficient is:
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Can r lie outside -1 and 1 range depending on the type of data?
Does correlation imply causation?
When is rank correlation more precise than simple correlation coefficient?
Does zero correlation mean independenc?
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