|
Observed |
Oi |
<25000 |
25000-50000 |
50000-75000 |
>75000 |
Total |
|
male |
25 |
47 |
48 |
36 |
156 |
|
|
female |
16 |
103 |
32 |
23 |
174 |
|
|
Total |
41 |
150 |
80 |
59 |
330 |
|
|
|
|
|
|
|
|
|
Expected |
Ei=?row*?column/?total |
<25000 |
25000-50000 |
50000-75000 |
>75000 |
Total |
|
|
male |
19.3818 |
70.9091 |
37.8182 |
27.8909 |
156 |
|
female |
21.6182 |
79.0909 |
42.1818 |
31.1091 |
174 |
|
|
Total |
41 |
150 |
80 |
59 |
330 |
|
|
|
|
|
|
|
|
| chi
square ?2 |
=(Oi-Ei)2/Ei |
<25000 |
25000-50000 |
50000-75000 |
>75000 |
Total |
|
male |
1.6285 |
8.0617 |
2.7413 |
2.3577 |
14.789 |
|
|
female |
1.4601 |
7.2277 |
2.4577 |
2.1138 |
13.259 |
|
|
Total |
3.089 |
15.289 |
5.199 |
4.471 |
28.0483 |
step 1:null hypothesis:salary and gender are independent
alternate hypothesis:Ha salary and gender are not
independent
Step 2 of 8: expected value for the number of men with an income
below $25,000 =19.4
Step 3 :expected value for the number of men with an income
$50,000-$75,000=37.8
Step 4 of 8: value of the test statistic. =28.048
Step 5 of 8:
|
degree of freedom(df) =(rows-1)*(columns-1)= |
3 |
Step 6 of 8:
|
for 3 df and 0.01 level of signifcance critical
region ?2= |
|
11.345 |
Step 7 of 8:
reject the null hypothesis
Step 8 of 8:there is sufficient evidence........
