What does it mean if the chi square test statistic has a value of zero?
Zero represents the null hypothesis. If all your observed frequencies equal the expected frequencies exactly, the chi-squared value for each cell equals zero, and the overall chi-squared statistic equals zero. Zero indicates your sample data exactly match what you’d expect if the null hypothesis is correct.
Would it be possible to obtain a calculated chi-square value of zero yes or no?
Often, chi-square values are numbers like “32.87” or “116.2”. The smallest chi-square value possible is 0, but there is no upper bound: it depends on the size of the numbers. Chi-square is zero only when there is absolutely no difference between the observed and the expected.
When do you ignore the 0’S in chi squared?
So I would do: You would only ignore the 0’s if there is some reason (not a statistical one) to do so; but including it would only change the degrees of freedom since (0-0) is, of course, 0. However, I am not sure you want chi-square here at all. It would depend on why you expected only AA genotype.
What are the results of the chi square test?
The key result in the Chi-Square Tests table is the Pearson Chi-Square. The value of the test statistic is 3.171. The footnote for this statistic pertains to the expected cell count assumption (i.e., expected cell counts are all greater than 5): no cells had an expected count less than 5, so this assumption was met. .
Which is the bad cell in the chi square?
Only one of the cells is really bad—that point on the lower-right—but it has a high expected value (it’s one of the largest cells in the table), and when you take the equally-weighted mean square (which is equivalent to weighting the contributions to the chi-square in proportion to the expected count), you get a big total value.
Why does the chi square distribution have low probability?
Thus, as the sample size for a hypothesis test increases, the distribution of the test statistic approaches a normal distribution. Just as extreme values of the normal distribution have low probability (and give small p-values), extreme values of the chi-square distribution have low probability.