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7. To test whether there is a significant difference in the mean weekly earnings between males and females (i.e., whether gender affects mean earnings), you regress weekly earnings on a constant and a binary variable, which takes on a value of 1 for females and is 0 otherwise. The results were (standard errors are in the parentheses): Ear = 610.5 + 160.2 • Female (9.4) (12.6) n = 5000, R2 = 0.086 (b) Are these results evidence enough to argue that there is discrimination against females? Why or why not? Your answer: The evidence is enough to argue that there is discrimination. not enough to argue that there is discrimination. The reason is bias. (I need two words here)

7. To test whether there is a significant difference in the mean weekly earnings between males and females (i.e., whether gender affects mean earnings), you regress weekly earnings on a constant and a binary variable, which takes on a value of 1 for females and is 0 otherwise. The results were (standard errors are in the parentheses): Ear = 610.5 + 160.2 • Female (9.4) (12.6) n = 5000, R2 = 0.086 (b) Are these results evidence enough to argue that there is discrimination against females? Why or why not? Your answer: The evidence is enough to argue that there is discrimination. not enough to argue that there is discrimination. The reason is bias. (I need two words here)

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.5: Comparing Sets Of Data
Problem 14PPS
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7. To test whether there is a significant difference in the mean weekly earnings between males and females (i.e., whether gender affects mean earnings), you regress weekly earnings on a constant and a binary variable, which takes on a value of 1 for females and is 0 otherwise. The results were (standard errors are in the parentheses): Ear = 610.5 + 160.2 • Female (9.4) (12.6) n = 5000, R2 = 0.086 (b) Are these results evidence enough to argue that there is discrimination against females? Why or why not? Your answer: The evidence is enough to argue that there is discrimination. not enough to argue that there is discrimination. The reason is bias. (I need two words here)
Transcribed Image Text:7. To test whether there is a significant difference in the mean weekly earnings between males and females (i.e., whether gender affects mean earnings), you regress weekly earnings on a constant and a binary variable, which takes on a value of 1 for females and is 0 otherwise. The results were (standard errors are in the parentheses): Ear = 610.5 + 160.2 • Female (9.4) (12.6) n = 5000, R2 = 0.086 (b) Are these results evidence enough to argue that there is discrimination against females? Why or why not? Your answer: The evidence is enough to argue that there is discrimination. not enough to argue that there is discrimination. The reason is bias. (I need two words here)
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