Different populations postulated to be normal

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The data in the following table (Exercise 12.12) shows samples of size = 20 drawn from four different populations postulated to be normal, , lognormal L, gamma G, and inverse gamma I, respectively.

XN

9.3745

XL

7.9128

XG

10.0896

XI

0.084029

8.8632

5.9166

15.7336

0.174586

11.4943

4.5327

15.0422

0.130492

9.5733

33.2631

5.5482

0.115567

9.1542

24.1327

18.0393

0.187260

9.0992

5.4151

17.9543

0.100054

10.2631

16.9556

12.5549

0.101405

9.8737

3.9345

9.6640

0.100835

7.8192

35.0376

14.2975

0.097173

10.4691

25.1182

4.2599

0.141233

9.6981

1.1804

19.1084

0.060470

10.5911

2.3503

7.0735

0.127663

11.6526

15.6894

7.6392

0.074183

10.4502

5.8929

14.1899

0.086606

10.0772

8.0254

13.8996

0.084915

10.2932

16.1482

9.7680

0.242657

11.7755

0.6848

8.5779

0.052291

9.3790

6.6974

7.5486

0.116172

9.9202

3.6909

10.4043

0.084339

10.9067

34.2152

14.8254

0.205748

(i) Validate these postulates using the full data sets. Note that the population parameters have not been speci?ed.

(ii) Using only the top half of each data set, repeat (i). For this particular example, what effect, if any, does sample size have on the probability plots approach to probability model validation?

Reference no: EM131002794

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