Q&A Hero

Q: When the correlation between two variables is +0.92, this means that as one variable ______ , the other variable ______. A.decreases; increases B.increases; stays the same C.increases; increases D.decreases; stays the same

Q: If the correlation between two variables is - 0.85, this means that ____. A.there is a weak positive relationship between the variables B.there is a strong inverse relationship between the variables C.there is a weak negative relationship between the variables D.there is a strong positive relationship between the variables

Q: If there is no relationship between two variables, the correlation coefficient between them would be _____. A.+1.0 B.-1.0 C.+0.50 D.0

Q: The Pearson product-moment correlation coefficient ranges between _____. A.zero and +1.0 B.-1.0 and zero C.-1.0 and +1.0 D.-2.0 and +2.0

Q: The Pearson product-moment correlation requires what type of scale for the data? A.nominal B.interval C.ordinal D.all of these choices

Q: The extent to which a change in one variable corresponds systematically to a change in another is called _____. A.spurious association B.significance C.covariance D.standardized coefficient

Q: A(n) _____ is a statistical measure of the covariation, or association, between two at-least interval variables. A.alpha coefficient B.beta coefficient C.correlation coefficient D.c2

Q: A bivariate statistical technique that is used to measure the strength of the relationship between two variables is called a _____. A.one-group t-test B.two-group t-test C.measure of association D.correlation matrix

Q: When the on-time performance of airlines is used to predict the number of customer complaints in a regression equation, on-time performance is the ______ variable and the number of customer complaints is the ______ variable. A.independent; dependent B.dependent; dependent C.dependent; independent D.independent; predictor

Q: If the regression weight is in the hypothesized direction, the hypothesis is supported.

Q: The first step in interpreting simple regression output is to interpret the individual parameter coefficient.

Q: A rule of thumb for R2 is that it must be greater than 0.80 for a regression model to be significant.

Q: The coefficient of determination reflects the proportion of variance that can be explained by the regression line.

Q: The statistical significance of a regression model is determined by a F-test.

Q: The least-squares regression line minimizes the sum of the squared deviations of the actual values from the predicted values in the regression line.

Q: The ordinary least-squares method of regression analysis is based on the logic of how much better a regression line can predict values of Y compared to simply using the standard deviation as a prediction.

Q: One way to determine the relationship between X and Y is to simply visually draw the best-fit straight line through the points in the figure.

Q: If the purpose of the regression analysis is forecasting, then standardized regression estimates must be used.

Q: In regression, the standardized Y-intercept term is always 0.

Q: In simple regression, standardized parameter estimates reflect the measurement scale range.

Q: In most business research, the estimate of b in a regression equation is most important.

Q: In a regression equation, the slope of the line, b, is the change in X that is due to a corresponding change of one unit of Y.

Q: In regression analysis, the equation of a straight line is Y = a + b X.

Q: The statistical significance of a correlation can be tested using the t-test.

Q: In a correlation matrix, the main diagonal contains correlations of 1.00 because it represents a variable's correlation with itself.

Q: A correlation matrix is the standard form for reporting observed correlations between two variables.

Q: The square of the correlation coefficient indicates the part of the total variance of dependent variable that can be accounted for by the independent variable.

Q: The correlation coefficient, r, indicates the magnitude of the linear relationships but not the direction of that relationship.

Q: A Spearman correlation is more appropriate for interval and ratio data than is the Pearson product-moment correlation.

Q: The symbol for the Pearson product-moment correlation coefficient is b.

Q: If r = -0.88, this indicates a weak relationship between the two variables under study.

Q: Covariance is the extent to which one variable causes a change in another variable.

Q: A correlation coefficient is a measure of the covariance, or association, between two at-least interval variables.

Q: Measure of association is a general term that refers to causality.

Q: Which of the following is a requirement for using the Z-test for differences of proportions? A.common sample B.degrees of freedom of at least 50 C.sample size greater than 30 D.ratio measurement of all variables

Q: Which test is appropriate for comparing the scores of two interval variables drawn from related populations? A.ANOVA B.relative t-test C.relative c2 test D.pair-samples t-test

Q: In practice, what is the first step in interpreting the t-test when comparing two means? A.compute the t-test value B.find the p-value associated with the t and the corresponding degrees of freedom C.examine the difference in means to find the "direction" of any difference D.examine if there is a difference at the 50 percent confidence interval before examining the 95 percent confidence interval

Q: In a study comparing the means of two groups in which there are 45 males in Group 1 and 37 females in Group 2, the degrees of freedom for this study when using the t-test for the difference between means is: A.84 B.80 C.82 D.160

Q: In using the t-test to compare the means of two groups, the degrees of freedom are calculated as _____. A.n1 - n2 - 2 B.n1 + n2 - 2 C.n1 x n2 -2 D.n1 / n2 - 2

Q: Suppose that you used a 9-point rating scale and that you wanted to compare men who had an annual income over $50,000 (Group 1) with men who had an annual income less than or equal to $50,000 (Group 2) on their liking of a new product. If you studied 40 men in Group 1 and they have a mean of 7 and a standard deviation of 2.5, while the 35 men in Group 2 have a mean of 5 and a standard deviation of 1.4, what is the approximate value of t using the t-test? A.3.43 B.4.19 C.2.64 D.not enough information to determine

Q: Supposed you used a 10-point rating scale to measure intention-to-buy (1 = definitely would not buy and 10 = definitely would buy). If a group of 40 males had a mean of 7 and a standard deviation of 2.5, while a group of 35 females had a mean of 5 and a standard deviation of 1.4, the standard error of the difference between the means would be approximately _____. A.0.48 B.1.36 C.2.45 D.not enough information to determine

Q: A(n) _____ is a test for hypotheses stating that the mean scores from some interval- or ratio-scaled variable group based on some less-than interval classificatory variable are not the same. A.regression B.cluster analysis C.c2 test D.independent samples t-test

Q: When a researcher needs to compare means for a variable grouped into two categories based on some less-than interval variable, a(n) _____ is appropriate. A.p-test B.t-test C.c2 test D.univariate test

Q: In order to use the chi-square test, the expected frequency in each of the cells of the contingency table should be at least _____. A.2 B.5 C.30 D.40

Q: In a brand awareness study, if 25 of a group of 35 males identify the brand correctly and 15 of a group of 35 females identify this brand correctly, the chi-square value for this study is approximately _____. A.3.26 B.4.15 C.5.84 D.2.92

Q: If 25 of the 35 females in a research study agree with a statement, and 15 of the 35 males agree with this statement, the expected value for males-agree is _____. A.15 B.20 C.25 D.35

Q: how do you determine the degrees of freedom in a four-cell chi-square test? A.(R + 1) B.(R - 1) C.(R - 1)(C - 1) D.R(C - 1)

Q: The formula for the chi-square test uses _____. A.observed and expected frequencies B.observed and expected percentages C.the two sample means D.the two sample standard deviations

Q: The formula given below represents the method for calculating the _____. A.Z-test B.F-test C.c2 test D.a

Q: All of the following are true regarding cross-tabulation EXCEPT _____. A.The c2 distribution provides a means for testing the statistical significance of a contingency table. B.The c2 for a contingency table compares two means that are not from independent samples. C.Cross-tabulations are much like tallying. D.The c2 test for a contingency table involves comparing the observed frequencies with the expected frequencies in each cell of the table.

Q: A researcher hypothesizes that males and females differ with respect to attitude toward sports sponsorships. To investigate this hypothesis that these two groups' attitudes differ, he will use a _____. A.bivariate test of differences B.univariate test of differences C.multivariate test of differences D.cluster analysis

Q: A _____ is an investigation of a hypothesis stating that two (or more) groups differ with respect to measures on a variable. A.statistical conclusions B.descriptive analysis C.paired comparison D.test of differences

Q: Total variability is the calculated by dividing the within-group variance by the between-group variance.

Q: The F-test partitions the total variance into within-group variance and between-group variance.

Q: The total mean is the mean of a variable over all observations.

Q: The null hypothesis for an ANOVA test comparing the means of three groups is: m1 m2 m3.

Q: ANOVA involving only one grouping variable is often referred to as one-way ANOVA.

Q: A Z-test for differences of proportions requires a sample size greater than 100.

Q: A paired-sample t-test is an appropriate test for comparing the scores of two interval variables drawn from related populations.

Q: A t-test is not appropriate and should not be used when the sample size is greater than 30.

Q: The reason that means that appear to be not so close could be concluded to be statistically the same is due to the variance.

Q: The t-test assumes that the two population means are equal.

Q: The first basic step in interpreting t-test results is to find the p-value associated with a particular t and the corresponding degrees of freedom.

Q: When no direction of a relationship is stated in the hypothesis, a one-tailed test is appropriate.

Q: In practice, computer software is used to compute thet-test results.

Q: The degrees of freedom are calculated as d.f. = n - 1 when using the t-test for comparing two means.

Q: A pooled estimate of the standard error is a better estimate of the standard error than one based on the variance from either sample.

Q: Thet-test for comparing the means of two groups assumes that the data are in nominal scales.

Q: The independent samples t-test tests the differences between means taken from two independent samples or groups.

Q: The chi-square test requires that the expected frequency in each cell of the contingency table be at least 30.

Q: To use the chi-square test, both variables in a 2 x 2 contingency table must be measured on a ratio scale.

Q: The chi-square test requires the researcher to compare the observed frequencies of the groups with the expected frequencies of the groups.

Q: One way to test the significance of contingency tables is by means of the t-test.

Q: A cross-tabulation is a simple way to describe the relationships between two groups.

Q: The type of measurement, the nature of the comparison, and the number of groups to be compared influence the statistical choice.

Q: If a researcher is interested in whether males switch jobs more frequently than do females, this is an example of univariate statistics.

Q: Tests are bivariate tests of differences when they involve only two variables: a variable that acts like a dependent variable and a variable that acts as a classification variable.

Q: What is ANOVA and when is it the appropriate statistical technique? What test is used to determine significance? Give an example of a research question that can be analyzed using ANOVA.

Q: Explain what a Z-test for comparing two proportions is and the appropriate hypothesis.

Q: Discuss when a paired-samples t-test is appropriate and give an example of when it should be used.