Question

Consider the following situations, and answer each of the following multiple-choice questions. Indicate your answer next to each question. Possible answers are: A = it increases; B = it decreases; C = it stays the same; D = not enough information to say for sure. “Increase” or “decrease” refers to the numerical value of a variable, not its interpretation as stringent or lenient. Assume that nothing else about the data changes besides the factor(s) listed in the problem. No need to explain or justify your answers.F. What happens to the likelihood of rejecting the null hypothesis for any F test when S_W² increases?

F. What happens to the likelihood of rejecting the null hypothesis for any F test when S_W² increases?

G. What happens to c²_crit when alpha decreases in value from .05 to .01?

H. What happens to c²_obt as the observed frequencies in each cell diverge less and less from the expected counts?

I. What happens to c²_crit when the number of levels of both independent variables increase?

J. What happens to the power of an analysis when a non-parametric rank-order back-up test (like the Mann-Whitney U test) is used instead of its parametric counterpart (like an unpaired t test), assuming the assumptions of the parametric test were met?

K. If a Pearson correlation coefficient is negative, what happens to r² when the Pearson r becomes even more negative?

L. When only the units used to measure X and Y change (like from inches to centimeters) – but not the actual data – what happens to the value of the Pearson r?

M. In simple linear regression, if the Pearson correlation changes from 0 to a positive number, what happens to the slope of the best-fit line?

N. In simple linear regression, if the Pearson correlation changes from 0 to a negative number, what happens to the slope of the best-fit line?

Answer 1