Primary information is the information that has already been collected for some other
purpose.
Michelle Steward is a marketing professor at Wake Forest University. Michelle had
been asked by the administration to study a sample of classes at Wake to help the
university understand the student population better particularly in terms of factors that
differentiate students with high versus low GPAs. One of the questions asked was,
“What score did you earn (0 to 100) on the last test that you took?” and another
question in the study asked, “How much time, estimated in numbers of minutes, did you
study for the last test you took?” Michelle decided to run a cross-tabulation analysis on
these two questions. When she did, she also ran the chi-square test. The result was a
Pearson Chi-Square Value of 8.64 and a p value reported as a “Sig.” in SPSS of .03.
Michelle knew that this meant:
A) there was a significant, positive association between the two variables.
B) there was the presence of an association; the probability of supporting the null
hypothesis that there is no association is only 3 percent.
C) there was the presence of a negative association; the probability of supporting the
null hypothesis that there is no association is only 3 percent.
D) there was the presence of a positive, “very strong” association because the
probability of supporting the null hypothesis that there is no association is only .03
percent.
E) None of the above; Michelle should not have run a chi-square test because the two
variables are both metric.