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Here are data for height, measured in centimeters, among a group of 20 male coll

ID: 3220721 • Letter: H

Question

Here are data for height, measured in centimeters, among a group of 20 male college students and each one's father. The column labeled N gives the number of father/son pairs with each combination of heights. Answer the following questions, being sure to show your work clearly and concisely. (a) Calculate the correlation coefficient for height between fathers and sons for this group of students. (b) Infer the correlation coefficient for height between fathers and sons for the population of male college students. (c) Is the population correlation coefficient statistically significantly different from zero? Explain.

Explanation / Answer

(a) Pearson’s Correlation Co-efficient is calculated using the below formula:                               

                                             

Let,

X denote Height of Parent

Y denote Height of Child

In our case,

n=20

Thus, we have the below table for calculating Correlation Coefficient:

N

Parent (Xi)

Offspring (Yi)

Xi2

Yi2

XiYi

1

172

174

29584

30276

29928

2

175

175

30625

30625

30625

3

175

178

30625

31684

31150

4

176

170

30976

28900

29920

5

176

174

30976

30276

30624

6

176

177

30976

31329

31152

7

178

178

31684

31684

31684

8

179

176

32041

30976

31504

9

180

178

32400

31684

32040

10

180

179

32400

32041

32220

11

180

179

32400

32041

32220

12

180

181

32400

32761

32580

13

181

178

32761

31684

32218

14

181

178

32761

31684

32218

15

181

180

32761

32400

32580

16

182

172

33124

29584

31304

17

182

175

33124

30625

31850

18

183

175

33489

30625

32025

19

184

179

33856

32041

32936

20

184

185

33856

34225

34040

Total

3585

3541

642819

627145

634818

Therefore,

n = 20

xi = 3585

yi = 3541

xi2 = 642819

yi2 = 627145

xiyi = 634818

Substituting the above values in the formula we get,

                rxy = 0.4478

(b) Since the correlation between heights of fathers and their sons is 0.4478, it indicates that there's a moderate correlation between the two and the positive sign infers that height of son will tend to be more if height of father is more.

(c) We need to test if, rxy = 0 (two-sided test. We assume a significance level of 0.05, i.e. = 0.05)

Therefore, our hypothesis becomes

                Ho: rxy = 0

                H1: rxy 0

We use t-test to test the significance of correlation co-efficient. The t-statistic is given as follows:

               

where,

rxy = 0.4478

n = 20

Substituting the values in the above formula we get,

                t = 2.125

To test the significance of our t-statistics, we refer to the critical value of t-distribution at 5% significance level and n-2, i.e. 18, degrees of freedom, i.e. t(0.025,18) = 2.1. (0.025 is taken as we have a two-sided test at 0.05 significance level, i.e. 0.05/2 = 0.025)

Since, value of value of t-statistic (2.125) > critical value of t (2.1), we reject our null hypothesis (Ho) and conclude that our correlation coe-fficient is significantly different from 0.

N

Parent (Xi)

Offspring (Yi)

Xi2

Yi2

XiYi

1

172

174

29584

30276

29928

2

175

175

30625

30625

30625

3

175

178

30625

31684

31150

4

176

170

30976

28900

29920

5

176

174

30976

30276

30624

6

176

177

30976

31329

31152

7

178

178

31684

31684

31684

8

179

176

32041

30976

31504

9

180

178

32400

31684

32040

10

180

179

32400

32041

32220

11

180

179

32400

32041

32220

12

180

181

32400

32761

32580

13

181

178

32761

31684

32218

14

181

178

32761

31684

32218

15

181

180

32761

32400

32580

16

182

172

33124

29584

31304

17

182

175

33124

30625

31850

18

183

175

33489

30625

32025

19

184

179

33856

32041

32936

20

184

185

33856

34225

34040

Total

3585

3541

642819

627145

634818

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