Employee Number

55, 58, 57, 16, 34, 70, 69, 53, 22, 63, 44, 27, 46, 40, 9, 38, 43, 30, 51, 17, 66, 4, 36, 64, 7, 68, 23, 61, 39, 60, 18, 1, 20, 41, 47, 24, 42, 49, 54, 29, 3, 67, 26, 8, 32, 28, 48, 71, 37, 50, 13, 65, 52, 11, 2, 45, 21, 62, 25, 14

Annual Salary

29606, 49033, 47180, 53429, 44183, 53174, 53429, 24352, 54981, 42961, 53627, 52111, 56294, 47180, 43124, 49033, 51237, 35423, 35200, 46574, 37292, 53423, 49033, 53174, 24395, 57242, 62530, 53627, 56294, 53429, 58968, 32368, 53627, 46574, 49033, 27525, 52722, 55549, 27525, 24967, 52722, 41188, 56884, 24395, 27525, 44183, 49033, 44138, 40741, 51237, 56294, 37292, 50175, 53174, 53174, 53174, 49033, 26491, 24395, 49033

Gender

F, M, F, F, M, M, F, F, M, M, M, M, M, F, M, M, M, F, F, M, M, M, M, M, M, F, M, M, F, F, F, F, M, M, F, F, M, M, F, F, M, F, M, F, F, F, M, F, M, M, M, M, F, M, M, M, M, F, M, F

Age

34, 54, 45, 52, 41, 50, 44, 35, 47, 36, 52, 56, 49, 45, 48, 42, 58, 47, 38, 57, 47, 47, 53, 45, 30, 45, 50, 47, 44, 45, 61, 42, 47, 56, 53, 38, 38, 35, 40, 55, 47, 34, 47, 52, 35, 38, 43, 38, 47, 56, 49, 46, 42, 46, 54, 54, 54, 46, 31, 55

Experience

4, 10, 5, 5, 2, 10, 6, 1, 7, 3, 8, 5, 10, 5, 8, 10, 2, 4, 1, 8, 1, 1, 8, 5, 5, 7, 10, 10, 6, 7, 10, 3, 10, 8, 10, 3, 8, 8, 3, 6, 10, 3, 10, 6, 3, 5, 9, 2, 2, 1, 10, 0, 5, 4, 10, 10, 5, 7, 5, 10

Training Level

B, A, B, B, A, B, C, A, A, B, A, A, B, C, A, A, B, A, B, A, A, B, A, A, A, C, B, A, C, B, B, B, B, A, B, A, C, C, A, A, A, B, A, A, A, B, A, B, A, C, B, A, A, C, B, A, B, A, A, B

Use the data above to answer the following questions in detail.

Question 1

a) Use the variable "Age" to construct the confidence intervals for the estimate of population mean. Find the confidence interval for "Age" with"training level" (Code=A), at both 92% and 96% levels. Interpret your confidence intervals.

b) Did you make any assumptions when constructing your confidence intervals? If yes, which assumptions; if not, why?

Question 2

Consider the claim that the average years of working experience when the data were collected was equal to 5 years. Use the variable "Experience" to test this claim. (Use the 5% level of significance).

Question 3

a) Based on your data set, is the average annual salary of the male employees is significantly HIGHER THAN the average annual salary of the female employees?Test at the 10% level of significance.Note that SPSS only performs a 2-sided test.

b) Provide possible reasons why you should or should not expect to find a significant statistical difference between the annual salary of these 2 groups.

c) Based on your findings, how should you propose to address this salary gap? Explain your reasoning.

Question 4

a) Make a graph of multiple box-whisker plots of annual salary among the three training levels.Based on observing the graphs only (no other calculations): which training level generally earns more?

b) Are the distributions of annual salary approximately symmetric? Are the IQR (Interquartile Range) approximately equal? Are the ranges approximately the same?

c) Are the assumptions for the one-way ANOVA satisfied to test the average annual salary among training levels?

Question 5

(a) Find the means salary for each training level.In your opinion do you think the means salary are equal, or somewhat equal or somewhat not equal, etc.

(b) Determine whether there was a difference in the mean salary among the training levels (use 5% level of significance).

(c) At 5% level of significance, can you conclude that the population variances are equal?Compare/comment your result obtained in this question to your opinion in question 4.

(d) Use the Tukey procedure to examine mean salary differences among the training groups. What conclusions can you reach with respect to the mean salary differences? In your case, is it necessary to perform the Tukey procedure? Why or why not?