Chi-square tests are parametric in nature - requiring data

Question

Question 1.The distribution for the goodness of fit test equals k-1, where k equals the number of categories.
True
False

Question 2.While rejecting the null hypothesis for the goodness of fit test means distributions differ, rejecting the null for the test of independence means the variables interact.
True
False

Question 3.For a two sample confidence interval, the interval shows the difference between the means.
True
False

Question 4.The goodness of fit test requires the expected distribution to be equally distributed across the categories.
True
False

Question 5.The Chi-square test for independence needs a known (rather than calculated) expected distribution.
True
False

Question 6.Chi-square tests are parametric in nature - requiring data that fit a specific distribution/shape.
True
False

Question 7.Statistical significance in the Chi-square test means the population distribution (expected) is not the source of the sample (observed) data.
True
False

Question 8.Chi-square tests rarely have type I errors.
True
False

Question 9.The goodness of fit test can be used for a single or multiple set (rows) of data, such as comparing male and female age distributions with an expected distribution at the same time.
True
False

Question 10.Compared to the ANOVA test, Chi-Square procedures are not powerful (able to detect small differences).
True
False