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When calculating Pearson's Chi-square statistic for the association of two nominal variables, we can construct a contingency table that breaks the data down into k

When calculating Pearson's Chi-square statistic for the association of two nominal variables, we can construct a contingency table that breaks the data down into k x l categories, where k and l are the number of categories for each nominal variable. For example, one variable describes vaccinated or unvaccinated (2 categories) and one describes whether participants contracted the disease or not (2 categories). So the contingency table is broken into 4 groups: vaccinated and diseased; vaccinated and healthy; unvaccinated and diseased; unvaccinated and healthy.

To calculate the chi-squared statistic, we must know the observed and expected values for these kxl categories. What does the expected value represent?

Select one:

a.

The expected value if the total sample size is equally divided by the number of groups.

b.

The expected value if there is no association between the two nominal variables.

c.

The expected value if there is full association between the two nominal variables.

d.

The total of one category in the cell divided by the total of the other category in that cell.

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