Question

The table below shows the observed pollution indexes of air samples in two areas of a city. Test the hypothesis that the mean pollution indexes are the same for the two areas. Area A Area B 2.92 4.69 1.84 3.44 1.88 4.86 0.95 3.69 5.35 5.81 4.26 4.95 3.81 5.55 3.18 4.47 Questions 9: A local bank has three branch offices. The bank has a liberal sick leave policy, and a vice-president was concerned with employees taking advantage of this policy. She thought that the tendency to take advantage depended on the branch at which the employee worked. To see if there were differences in the time employees took for sick leave, she asked each branch manager to sample employees randomly and record the number of days of sick leave taken during 1990. Ten employees were chosen, and the data are listed below. Does this data indicate a difference in branches? Use a level of significance of 0.05. Branch 1 15 20 19 Branch 2 11 15 11 Branch 3 18 19

Answer 1

Answer:

Enter the values into one variable and the corresponding sample number (1 for Area A, 2 for

Area B) into another variable (see upper-left figure, below). Be sure to code your variables

appropriately. Now it is time to check the normality assumption. Select “Split File” from the

“Data” menu so that we can tell SPSS that we want separate Q–Q Plots for each group (see

upper-right figure, below). Select “Organize output by groups” and enter “area” as the variable

that groups are based upon (see lower-left figure, below). Now create Normal Q–Q Plots to

assess the normality of each group (see separate handout on Normal Q–Q Plots). Once you’ve

created your Q–Q Plots and determined that your groups are approximately normally distributed,

select “Split File” from the “Data” menu and then select “Analyze all cases, do not creat