Use a χ2 test to test the claim that in the given contingency table, the row variable and the column variable are independent. Responses to a survey question are broken down according to gender and the sample results are given below. At the 0.05 significance level, test the claim that response and gender are independent.
male: 25, 50,15
female: 20,30,10
test statistic
critical value
accept or reject
Applying chi square test of independence: |
Expected | Ei=row total*column total/grand total | x1 | x2 | x3 | Total |
male | 27.0000 | 48.0000 | 15.0000 | 90.00 | |
female | 18.0000 | 32.0000 | 10.0000 | 60.00 | |
total | 45.00 | 80.00 | 25.00 | 150.00 | |
chi square χ2 | =(Oi-Ei)2/Ei | x1 | x2 | x3 | Total |
male | 0.148 | 0.083 | 0.000 | 0.2315 | |
female | 0.222 | 0.125 | 0.000 | 0.3472 | |
total | 0.3704 | 0.2083 | 0.0000 | 0.579 | |
test statistic X2 = | 0.5787 |
for 2 df and 0.05 level , critical value χ2= | 5.991 |
since test statistic <critical value
accept
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