Lab6

1.

There are 5 variables with 474 entries.

2.

The variables included are Gender, Current.Salary, Years.Of.Education, Minority.Classification, and Date.of.Birth.

3.

The new dimensions of the filtered dataset are 5 variables with 116 entries.

4.

The null hypothesis in this case is that the mean salary does not differ by sex in the population.

5.

Including only those with 15 years of education helps to control education as a confounding factor in mean salary.

6.

The t-statistic is equal to 5.0443.

7.

The p-value is equal to 1.977e-06.

8.

The limits of the 95% confidence interval are 3930.779 and 9024.884

9.

The confidence interval does not contain the value 0.

10.

The mean value of salaries for men with 15 years of education is 33,527.83, and the mean value of salaries for women with 15 years of education is 27,050.

11.

Given the values of the t-statistic, p-value, and that the confidence interval does not contain the value zero, I would conclude to reject the null hypothesis; the mean salary for the population does appear to differ by sex.

12.

The t-statistic is equal to -2.4432.

13.

The p-value is equal to 0.01755.

14.

The limits of the 95% confidence interval are -6673.2519 and -644.4916.

15.

The confidence interval does not contain the value 0.

16.

The mean salary for minorities with 15 years of education is 28,838.46, and the mean salary for non-minorities with 15 years of education is 32,507.33

17.

Considering the t-statistic, the p-value, and the confidence interval not containing 0, I would conclude to reject the null hypothesis; the mean salary for the population does appear to vary by minority classification.

18.

There does appear to be a significant difference in means for salaries for minority and non-minority men at 95%. (t= -5.5845, p=9.209e-08)

19.

There does appear to be a significant difference in means for salaries for minority and non-minority women at 95% (t= -4.1825, p=5.478e-05)

20.

Mean Salaries	Male	Female
Non-minority	44,475.41	26,706.79
Minority	32,246.09	23,062.50

23.

EmployeeNum <- read.csv("employeenumeric.csv")
Ed15 <- EmployeeNum[EmployeeNum$Years.of.Education==15,]
interaction.plot(Ed15$Gender, Ed15$Minority.Classification, Ed15$Current.Salary)

The interaction plot shows that non-minority men and women have a higher mean salary than minority men and women and that males have higher average salaries than females.