Exam 13: Analysis & Interpretation: Multiple Variables Simultaneously

Given a cross tabulation between years of education and income, we would compute percentages in the direction of years of education because:

A researcher is interested in comparing the usage of bank debit cards by consumers in rural (r) and urban (u) areas. Each year for the past five years, she has surveyed 500 individuals (one-half urban, one-half rural) randomly selected from across the United States. She is specifically interested in any differences that may exist between the two groups with regard to usage. The results of the current study indicate that people in urban areas use bank debit cards 12 times per month on average( ), while those in rural areas use bank cards 10 times per month on average ( ). -Refer to Exhibit 13.2. Which of the following is the null hypothesis that the researcher should use in comparing the usage rates?

-Refer to Exhibit 13.1. The above table is an example of

If the correlation between two variables x and y is equal to -0.90, which of the following is TRUE?

Compare and contrast the use of analysis of variance (ANOVA) versus conducting a series of t-tests to examine differences across groups.

A statistic used to measure the strength of relationship between categorical variables is called a Cramer's V.

Percentages are always calculated in the direction of the causal variable.

Suppose you were given an example of running a chi-square test using SPSS. The output shows a "Pearson Chi-Square" value of 82.123, df = 3 and the Asymp. Sig. = 0.000. This means:

In order to use the pooled sample variance when testing the difference in two population means, what must be assumed?

-Refer to Exhibit 13.1. In absolute numbers, how many millions of households own a microwave?

Suppose that the relationship between sales (Y, in $000) and number of salespeople (X) is represented by the following regression equation: Y = 105.2 + 35.8X -Refer to Exhibit 13.3. What will be the average contribution to sales of one additional salesperson?

A factorial design is an ANOVA analysis that includes two or more dependent variables.

A researcher is interested in comparing the usage of bank debit cards by consumers in rural (r) and urban (u) areas. Each year for the past five years, she has surveyed 500 individuals (one-half urban, one-half rural) randomly selected from across the United States. She is specifically interested in any differences that may exist between the two groups with regard to usage. The results of the current study indicate that people in urban areas use bank debit cards 12 times per month on average( ), while those in rural areas use bank cards 10 times per month on average ( ). -Refer to Exhibit 13.2. Given that the critical value that the test statistic is to be compared with is equal to 1.645 at a 90% significance level, which of the following statements are true?

An analyst has a set of normally distributed intervally scaled data resulting from two observations on the same sample of subjects, and he wishes to investigate if there is any difference in these two means. The appropriate statistical procedure is:

Suppose the ordinary least-squares approach to a regression analysis produced the following: Y = 20 - 39X R² = .90 Which of the following statements is FALSE?

In testing a multiple regression equation for statistical significance, the first step involves:

Assume that a researcher determines that a p-value of 0.01 or below determines significance. Listed below are several correlation coefficients and their respective significance levels. Which correlation coefficient demonstrates an association not likely due to chance (i.e., significant)?

The error term in the regression model represents all factors that determine criterion variable that are not part of the model.

Suppose that the relationship between sales (Y, in $000) and number of salespeople (X) is represented by the following regression equation: Y = 105.2 + 35.8X -Refer to Exhibit 13.3. What will average sales be equal to when 10 salespeople are used?

Let's assume we find in a study that the Pearson's correlation coefficient between number of years of education and cigarette smoking is -0.73. This means that as education level increases: