Lab6

Question 1

The data set is 474 rows by 5 columns

Question 2

The variables included in the data are gender, current salary, years of education, minority classification, and date of birth

Question 3

The dementions of the new data frame are 116 by 5.

Question 4

The null hypothesis is there is the difference between men and women current salary is random and gender has no factor into the salary.

Question 5

Education usually has a great impact on income so it is important to make it a control variable to stop it from influencing the gender results.

Question 6

The t-statistic for the difference in salaries between men and women with 15 years of education is 5.0443.

Question 7

The p-value is 1.977e-06.

Question 8

The limits of the 95% CI are 3930.779, 9024.884.

Question 9

The CI does not contain zero.

Question 10

The mean salaries for men is 33527.83 and for women is 27050.00.

Question 11

It can be concluded from the p-value less than 0.05 and the confidence interval that the null hypothesis is rejected. It can be concluded that there is a significant difference between men and women with 15 years of education current salaries due to gender.

Question 12

the t-statistic for the difference in salaries between minority and non-minority respondents with 15 years of education is -2.4432.

Question 13

The p-value is 0.01755.

Question 14

The limits of the 95% CI are -6673.2519, -664.4916.

Question 15

The CI does not contain zero.

Question 16

The mean salary for minorities is 28838.46 and for non-minorities is 32507.33.

Question 17

Since the p value is less than 0.05 and the CI does not include zero, the null hypothesis can be rejected. It can be concluded that there is a significant difference between minority statuses in salaries.

Question 18

Yes, there is a significant difference between non minority and minority men’s salaries because the p-value is less than 0.05 and the CI does not include zero.

Question 19

No, there is not a significant difference between non minority and minority women’s salaries because the p-value is greater than 0.05 and the CI does include zero.

Question 20

Mean Salaries	Male	Female
Non-Minority	33527.83	27050.00
Minority	30055.56	26100.00

Question 23

employeenumeric <- read_excel("C:/Users/Charlotte Zimmerman/Desktop/GEOG391/Lab6/employeenumeric.xls")
View(employeenumeric)
edu15 <- employeenumeric[employeenumeric$`Years of Education` == 15, ]
attach(edu15)
interaction.plot(Gender, `Minority Classification`, `Current Salary`)

This plot shows how minority status interacts with gender differently. Overall, men made more than women, but the difference between minority men and non minority men was greater than the difference with women. Minority women made less overall, but the difference between non minority women was not as extreme.