Mia has had several of her customer service front bakery representatives quit. Before you hire more employees, Mia wants to know if there is disparate impact occurring for the customer service positions throughout the bakeries. Analyze the data below, by applying the 4/5ths rule to determine if disparate impact has occurred.

To do this, calculate disparate impact for both gender and race. Use the 3.00 rating as the cutoff score for those who get the job (selected).

To calculate disparate impacts using the 4/5ths analysis, start by calculating 80% of the majority selection rate, and compare it with the group selected at a lower rate. Here is an example for gender:

Gender 0=26 out of 35 have a cut score of 3.00 or higher and were selected. 26/35=.74, or 74%.

Gender 1=20 out of 29 have a cut score of 3.00 or higher, and were selected. 20/29=.69, or 69%.

The selection rate of Gender 1 is less than that of Gender 0. The selection rate for Gender 1 needs to be at least 80% of Gender 0 (74%). So we calculate 80% * 74%=59%. Gender 0 is selected at 69%, that is higher than 59%, so there is no evidence of disparate impact.

Employee #	Gender	Race	Rating
63	1	1	1.46
7	1	1	1.58
16	0	1	2.08
18	0	1	2.08
42	0	1	2.08
17	1	1	2.15
51	1	1	2.18
2	0	1	2.25
22	0	1	2.28
35	1	0	2.35
26	0	1	2.38
5	1	0	2.42
62	0	1	2.45
48	0	0	2.48
23	1	0	2.5
53	1	1	2.58
69	1	1	2.65
58	0	0	2.68
19	1	1	2.85
11	1	0	2.9
25	1	1	2.95
3	1	1	2.98
24	0	0	3.08
33	1	1	3.08
49	1	1	3.08
64	0	0	3.08
31	1	1	3.18
50	0	1	3.28
4	0	0	3.48
55	1	1	3.58
27	1	0	3.68
36	0	0	3.68
20	0	0	3.78
21	1	0	3.78
29	1	0	3.78
32	0	1	3.78
45	1	1	3.78
52	0	0	3.78
70	0	0	3.78
10	0	0	3.88
34	0	0	3.88
41	1	0	3.88
47	1	0	3.88
65	1	0	3.88
14	0	0	4.18
30	0	0	4.18
56	0	0	4.18
61	1	1	4.18
68	0	1	4.18
54	0	0	4.3
9	1	1	4.48
15	1	1	4.48
40	0	0	4.48
38	0	1	4.58
46	0	0	4.58
60	0	0	4.58
67	1	1	4.58
8	0	1	4.68
39	1	1	4.68
57	1	1	4.68
6	0	0	4.88
13	1	1	4.88
37	1	1	4.88
44	0	0	4.88
1	1	1	4.98
12	0	0	4.98
28	0	0	4.98
43	1	1	4.98
59	1	0	4.98
66	0	0	4.98