Question

1. The data below shows the life expectancy of men and women in different countries:

	LifeExpMale	LifeExpFemale
Argentina	74	67
Bangladesh	53	54
Brazil	68	62
Canada	80	73
China	72	68
Colombia	74	68
Egypt	61	60
Ethiopia	53	50
France	82	74
Germany	79	73
India	58	57
Indonesia	63	59
Iran	65	64
Italy	82	75
Japan	82	76
Kenya	63	59
Korea.North	73	67
Korea.South	73	67
Mexico	76	68
Morocco	66	63
Burma	56	53
Pakistan	57	56
Peru	67	62
Philippines	67	62
Poland	77	69
Romania	75	69
Russia	74	64
South.Africa	67	61
Spain	82	75
Sudan	54	52
Taiwan	78	72
Tanzania	55	50
Thailand	71	66
Turkey	72	68
Ukraine	75	66
UK	79	73
USA	79	72
Venezuela	78	71
Vietnam	67	63
Zaire	56	52

a. what test should you use to test the two data sets (male and female life expectancy) for normality and why? (2 points)

b. Run that test on both variables.   Report the results below (2 points).  

3. What do you conclude in each case. Explain! (2 points)

4. Should you use a Pearson’s or a Spearman’s Rank Correlation for this data? Why? (2 points)

e. Calculate the correlation coefficient using SPSS. What is the value of r for this data set? (2 points)

6. What do you conclude about the type of correlation (positive / negative, significant / non-significant)? Explain using information from the SPSS output (3 points)

Answer 1

a. what test should you use to test the two data sets (male and female life expectancy) for normality and why? (2 points)

The Anderson-Darling test because it gives the normality information correctly.

b. Run that test on both variables.   Report the results below (2 points).  

1. What do you conclude in each case. Explain! (2 points)

Males' data is not normally distributed.

1. Should you use a Pearson’s or a Spearman’s Rank Correlation for this data? Why? (2 points)

Pearson’s Correlation because the data is not ranked.

e. Calculate the correlation coefficient using SPSS. What is the value of r for this data set? (2 points)

r = 0.979

1. What do you conclude about the type of correlation (positive / negative, significant / non-significant)? Explain using information from the SPSS output (3 points)

There is a strong positive significant relationship between the variables.