Which of the following are TRUE?
I.A chi-square test of independence is essentially the nonparametric version of the interaction term in ANOVA.
II.A chi-square test of independence requires more than two variables.
III.Expected cell frequencies should all be less than 1.
IV.No more than 20% of the categories should have less than 5 expected frequencies.
V.Two variables are independent if knowing the outcome of one tells you nothing about the outcome of the other.
VI.Two variables are independent if knowing the outcome of one tells you something about the outcome of the other.
A)I, II, & III only
B)II, III, IV only
C)II, III, & VI only
D)III, IV, & V only
E)I, IV, & V only

Question

Quizplus · Accepted Answer

I. A chi-square test of independence can indeed be seen as a nonparametric counterpart to testing for interaction effects in factorial ANOVA, as both assess the relationship between categorical variables.IV. The guideline for chi-square tests is that no more than 20% of expected frequencies should be less than 5, to ensure adequate power and the validity of the chi-square approximation to the true distribution.V. Independence between two variables means that the outcome of one does not provide any information about the outcome of the other, which is exactly what the chi-square test of independence tests for.

Which of the Following Are TRUE