Complete the following steps to interpret a chi-square test of association. Key output includes p-values, cell counts, and each cell's contribution to the chi-square statistic.
In these results, the Pearson chi-square statistic is 11.788 and the p-value = 0.019. The likelihood chi-square statistic is 11.816 and the p-value = 0.019. Therefore, at a significance level of 0.05, you can conclude that the association between the variables is statistically significant.
To determine which variable levels have the most impact, compare the observed and expected counts or examine the contribution to chi-square
By looking at the differences between the observed cell counts and the expected cell counts, you can see which variables have the largest differences, which may indicate dependence. You can also compare the contributions to the chi-square statistic to see which variables have the largest values that may indicate dependence.
|1st shift||2nd shift||3rd shift||All|
In this table, the cell count is the first number in each cell, the expected count is the second number in each cell, and the contribution to the chi-square statistic is the third number in each cell. In these results, the expected count and the observed count are the largest for the 1st shift with Machine 2, and the contribution to the chi-square statistic is also the largest. Investigate your process during the 1st shift with Machine 2 to see if there is a special cause that can explain this difference.