Therefore, "van" contributes nothing to the resulting chi-square value all the divergence in the data comes from the "sedan" and "truck" categories. The "sedan" and "truck" categories did not meet their expectation, but "van" did. For example, if a goodness-of-fit test rejects the null hypothesis, is this outcome caused by all categories differing moderately from their expectations, or to a single category differing strongly from its expectation? For example, suppose you expect a sample of 100 cars in a very large parking lot to contain 50 sedans, 27 trucks, and 23 vans, but instead it contains 61 sedans, 16 trucks, and 23 vans. To use Minitab to analyze these, YOU MUST TYPE IN the summary table into the Minitab. Below you can see that we have one column with the names of each group and one column with the observed counts for each group. To perform a chi-square goodness-of-fit test in Minitab using summarized data we first need to enter the data into the worksheet. If the p-value associated with your chi-square statistic is less than your selected α, the test rejects the null hypothesis that the model fits the data.įor categorical data, Minitab can report each category's contribution to the chi-square value, which quantifies how much of the total chi-square value is attributable to each category's divergence. For this, you must use Stat > Tables > Chi-Squared Test for Association. Summarized Data, Equal ProportionsSection.
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