Pivot Table and Chi Square Hypothesis Test

Using the "Cumba" database file, create a pivot table of management level versus gender. Then copy the data from the table into a chi square table to see if a relationship exists between employee genders and their management level. What can you conclude at the .05 significance level?

Salary (dollars) Gender Age (years) Experience (years) Management Level Education Level
41,711 F 30 0 2 0
27,739 F 26 1 1 0
67,977 M 42 3 3 1
32,950 F 38 6 1 0
72,899 F 43 4 3 1
30,096 F 32 4 1 0
42,513 F 32 2 2 0
48,630 F 38 5 2 0
51,450 M 37 7 2 1
46,319 F 36 5 2 0
74,425 M 47 4 2 2
62,426 M 41 1 3 0
29,495 F 30 3 1 0
58,297 F 43 13 2 1
40,470 M 44 13 1 0
77,395 F 50 7 2 2
41,410 M 37 15 1 1
47,300 F 30 0 2 1
26,074 M 23 2 1 0
26,451 F 24 3 1 0
25,367 F 21 0 1 0
25,820 F 22 1 1 0
32,008 M 37 5 1 0
27,996 M 28 2 1 0
45,999 M 42 19 1 1
48,924 F 33 0 2 1
46,986 F 37 5 2 0
79,550 M 50 0 3 2
72,464 F 45 0 2 2
39,932 F 33 12 1 1
55,869 F 41 9 2 1
52,045 F 39 8 2 1
26,208 M 23 0 1 0
30,344 F 33 4 1 0
58,054 M 42 11 2 1
68,133 M 51 14 2 1
31,529 F 35 5 1 0
35,565 F 39 7 1 0
35,986 M 40 8 1 0
24,539 F 21 0 1 0
25,623 M 21 0 1 0
44,956 F 41 18 1 1
31,298 F 34 4 1 0
28,141 F 28 2 1 0
29,926 M 31 3 1 0
60,136 F 46 10 2 1
26,527 F 25 4 1 0
56,140 F 41 10 2 1
43,992 M 34 3 2 0
28,429 F 29 2 1 0
54,800 M 54 19 1 2
37,474 M 41 10 1 0
29,631 F 31 3 1 0
55,784 F 40 9 2 1
31,497 F 35 5 1 0
54,429 F 40 8 2 1
31,795 F 36 5 1 0
94,541 M 55 9 3 2
36,716 F 21 0 1 1
62,361 F 47 11 2 1
69,750 M 52 15 2 1
44,314 M 39 17 1 1
49,405 F 42 14 1 2
76,986 M 48 6 2 2
31,995 F 36 5 1 0
31,301 M 35 5 1 0
39,850 F 42 11 1 0
59,644 M 44 15 2 1
49,073 M 39 7 2 0
37,128 F 28 6 1 1
66,708 F 49 13 2 1
38,666 F 29 7 1 1
44,690 F 35 4 2 0
47,955 M 32 0 2 1
31,002 F 34 4 1 0
42,204 M 31 1 2 0
80,456 M 54 10 2 2
49,042 F 36 7 2 1
77,154 M 45 5 3 1
25,019 M 21 0 1 0
64,741 M 40 0 3 1
46,047 F 40 0 1 2
52,175 F 49 18 1 2
30,621 M 33 4 1 0
49,357 F 40 7 2 0
27,514 M 26 5 1 0
27,987 F 27 1 1 0
25,738 F 22 0 1 0
64,756 F 48 12 2 1
41,077 F 36 14 1 1
37,118 F 41 9 1 0
51,759 F 38 8 2 1
97,431 M 57 10 3 2
85,594 F 53 8 3 2
85,457 M 52 6 3 2
32,589 M 37 6 1 0
28,643 M 30 3 1 0
51,987 F 45 16 1 2
33,803 F 39 6 1 0
43,186 M 38 16 1 1