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Marketing Research An Applied Orientation
Quiz 15: Frequency Distribution,cross-Tabulation,and Hypothesis Testing
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Question 41
True/False
Nonparametric tests are used when the independent variables are nonmetric.
Question 42
True/False
The F static is computed as the ratio of two sample variances.
Question 43
True/False
The runs test tests the goodness of fit of the observed number of observations in each category to the number expected under specified binomial distribution.
Question 44
True/False
In hypothesis testing,the observations are paired so that the two sets of observations relate to the same respondents.
Question 45
True/False
Paired samples are two samples that are not experimentally related.
Question 46
True/False
Hypothesis-testing procedures can be broadly classified as parameter or nonparameter based on the measurement scale of the variables involved.
Question 47
True/False
The McNemar test is another paired sample nonparametric test that is used in the special case of a binary variable where the researcher wishes to test differences in proportions.
Question 48
True/False
When measuring the strength of association with the contingency coefficient,the maximum value of 1 is achieved when the variables are perfectly associated.
Question 49
True/False
The two-sample median test is not as powerful as the Mann-Whitney U test.
Question 50
True/False
The two-sample median test examines whether the two distributions are the same.
Question 51
True/False
The critical value of the F distribution depends upon two sets of degrees of freedom: those in the numerator and those in the denominator.
Question 52
True/False
When conducting cross-tabulation analysis in practice,if H
0
is rejected,the pattern of the relationship should be interpreted by computing an appropriate statistic (phi coefficient,contingency,Cramer's V,lambda coefficient,or other statistics).
Question 53
True/False
When variables are perfectly associated,the phi coefficient assumes the value of 1.
Question 54
True/False
The Mann-Whitney U test is a statistical test for a variable measured on an ordinal scale,comparing the difference in the location of two populations based on observations from two independent samples.