Statistic Problem
The following data are based on numbers taken from the Bureau of Labor Statistics surveys from the year 2019 ( https://www.bls.gov/cps/aa2019/cpsaat39.htm ), for community, service, social science, and education occupations. They represent the average weekly pay for wage and salary earners measured during 2019 and broken down by gender. Enter these data into a new file containing one grouping variable for gender and one variable for salary.
For the Gender variable in column 1, code women as 1 and men as 2
Remember to define these in Value Labels as covered in the presentations.
There will be thirteen “1”s and thirteen “2”s (as many participants as in each group) in the Gender column in SPSS.
The corresponding earnings will be entered in the Salary column in SPSS.
Women Men
1358 1870
1042 1161
1095 1262
942 1190
579 707
1003 944
944 1108
862 1155
896 928
556 588
731 953
664 890
589 671
Using the data in the table above, set up your data file in SPSS and create a table of Descriptive Statistics using the “Explore” function that shows descriptives for women and men separately. Paste the table here: (8 pts)
What is the median salary for men in this sample? (5 pts)
What are the mean and of salaries for women? (5 pts)
Using the same data, create a boxplot in SPSS to show the difference in salaries between women and men. Paste the boxplot here: (6 pts)
Locate the outlier in the boxplot. What effect does this data point have on the mean of weekly earnings for men? (6 pts)