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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Please answer the following.

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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