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Professor Chastain is interested in the gender pay gap. This is the idea that women make less than men. However, a common complaint in response

Professor Chastain is interested in the "gender pay gap." This is the idea that women make less than men. However, a common complaint in response to this idea is that men and women work different jobs, and different jobs pay different amounts of money (so the gap is due to different jobs). To account for that, Professor Chastain collects data from 28 total jobs, looking at the salary for women and men for the SAME job (e.g., women engineers make $40,820, and men engineers make $55,432).

Profession

Women

Men

Engineering

40,820

55,432

Medical scientists

59,332

75,348

Software market research

52,104

65,988

... 28 total jobs

...

...

She gets a lot of numbers after running the statistics, including:

  • t = 12.38
  • p < 0.001
  • women make $51,021.29 on average with a standard deviation of 15460.72
  • men make $61,057.29 on average with a standard deviation of 17816.1
  • Cohen's d is 2.34
  • Plus, the df you found in the previous question

SHORT ANSWER (14 points): Using the template provided in the notes, how should she report and interpret the test results?

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