12.The chisquare contingency table is ideally suited for

a.determining whether two random samples come from populations with the same median.

b.analyzing observations on the same individual in a pretestposttest experiment.

c.an analysis that involves two related samples.

d.determining whether a given set of observations has indeed been drawn at random from a single population.

e.investigating the independence of variables in cross classifications.

13.Which of the following statements regarding contingency tables is FALSE?

a.To generate the expected frequencies for each cell in a chisquare contingency table test, one need simply multiply the marginal frequencies and divide by the total number of cases.

b.The marginal total of a row in a chisquare contingency table test is determined as the product of the expected frequencies for that row.

c.In a contingency table test, the null hypothesis is that the variables of classification are independent.

d.The expected number of cases in each cell in a contingency table test rest on the assumption that the variables of classification are independent.

e.When the observations forming the cross tabulation are related as in a beforeafter experiment, the chisquare contingency table is not applicable.

14.In a two-way contingency table with four rows and four columns, the appropriate degrees of freedom for the chi-square test statistic is

a.3, 3.

b.15.

c.3, 12.

d.9.

e.to determine the appropriate degrees of freedom one must known, the number of participants in the experiment.

17.Which of the following statements pertaining to the contingency coefficient is FALSE?

a.The contingency coefficient is directly related to the chisquare test.

b.Its upper value limit is determined by the number of categories in a problem.

c.Some of the difficulties encountered in interpreting the contingency coefficient are overcome by squaring the coefficient, thereby obtaining the proportion of variance in the criterion variable explained by the predictor variable.

d.The contingency coefficient as a measure of association is difficult to interpret purely by examining the calculated value.

e.The contingency coefficient provides a measure of the strength of the association between the variables.

18.A researcher interested in measuring the association between two nominally scaled attributes should use

a.the contingency coefficient.

b.t-test for nominal data.

c.Pearson's product moment correlation coefficient.

d.the coefficient of consistency.

e.none of the above.

19.The following formula is for:

a.the chisquare correction for attenuation.

b.the index of predictive association.

c.the chisquare test for distribution symmetry.

d.the contingency coefficient.

e.the coefficient of concordance.