In: Statistics and Probability
A manufacturer is considering purchasing parts from three different suppliers. The parts received from the suppliers are classified as having a minor defect, having a major defect, or being good. Test results from samples of parts received from each of the three suppliers are shown below. Note that any test with these data is no longer a test of proportions for the three supplier populations because the categorical response variable has three outcomes: minor defect, major defect, and good.
Supplier |
||||||
Part Tested | A | B | C | |||
---|---|---|---|---|---|---|
Minor Defect | 16 | 11 | 21 | |||
Major Defect | 6 | 10 | 6 | |||
Good | 140 | 126 | 116 |
Using the data above, conduct a hypothesis test to determine if the distribution of defects is the same for the three suppliers. Use the chi-square test calculations as presented in this section with the exception that a table with r rows and c columns results in a chi-square test statistic with (r-1)(c-1) degrees of freedom. Using a .05 level of significance, what is the p-value?
x^2=_________(2 decimals)
p-value __________
What is your conclusion?
Conclude that we are________(unable/able) to reject the hypothesis that the population distribution of defects is the same for all three suppliers
Expected value = sum of the that row* sum of that column/ total sum
Test statistic:
p-value = 0.2245
As p-value = 0.2245 > 0.05, we fail to reject the null hypothesis.
We are able to reject the hypothesis that the population distribution of defects is the same for all three suppliers.