1. In a 3 × 3 analysis of variance, the number of null hypotheses is:

A. 1

B. 3

C. 6

D. 9

2.

If an experimenter “crosses Intelligence with Attractiveness” in a factorial design in which intelligence has three levels (high, medium, and low) and attractiveness has two levels (high and low), the study will:

A. be a three-way analysis of variance.

B. be a 3 × 2 analysis of variance.

C. have eight cells to the third power.

D. have five cells.

3.

In a 2 × 2 analysis of variance, the basis for estimating the numerator of the F ratio for the column effects is:

A. the variance among the four cell means.

B. the variance between the two column marginal means.

C. the variance between the two row marginal means.

D. the variance between the means of the two diagonals.

4.

When considering the power of a main effect in a factorial analysis of variance, all of the following must be taken into account EXCEPT:

A. the number of scores per cell.

B. the number of levels of the other grouping variable.

C. the predicted effect size for this main effect.

D. the predicted effect size for the other grouping variable.

5.

The scenarios below are possible results of a study in which participants completed a measure of how important religion was to them personally. Participants are either from a Rural or Urban area, and are either Poor or Rich.

Which of the following interpretations is consistent with Scenario A?

A.

Religion is more important to poor people when they live in rural areas.

In the urban areas, poor people are socialized to be more like rich

people, who are less religious, regardless of where they live.

B.

Rich people, regardless of where they live, value religion moderately.

Poor people value religion more in urban centers than in rural areas

because it is more accessible.

C.

People who live in the urban areas need religion more than people in

rural areas, regardless of how rich or poor they are.

D.

Poor people in urban areas have a harder time than people in rural areas, so they value religion more. Rich people who move to rural areas are trying to get away from their materialistic lifestyle and tend to be more religious.

6.

In a two-way analysis of variance, what is the population variance estimate for the denominator of the F ratios for the main and interaction effects?

A. All effects are tested using the same estimate based on averaging the estimates of the variance of scores within each cell.

B. Each effect is tested using a variance estimate based on the variation

within the appropriate groupings.

C. Each effect is tested using a variance estimate based on the variation

among the appropriate marginal means.

D. The row and column effects are tested using an estimate based on the

variation within the appropriate groupings, but the interaction effect

is tested based on averaging the estimates based on variance of scores

within each cell.

7.

In a two-way factorial design, there can be:

A. one interaction and one main effect.

B. one interaction and two main effects.

C. two interactions and one main effect.

D. two interactions and two main effects.

8.

In a factorial analysis of variance, the effect size for each main and interaction effect:

A. is the same for each effect.

B. is the same number for row and column effects, but different for the interaction effect.

C. is different for each row, column, and interaction effect.

D. cannot be calculated because only an effect size for the overall combination of main and interaction effects can be calculated.

9.

What is the relationship between the amount of time spent shopping, Short (under 15 minutes) or Long (over 15 minutes), and the age of the shopper, Young (under 22) or Old (over 22), and the amount of money spent by shoppers in a music store.

A store manager said, “How much money people spend isn’t related to age. All that matters is how long they shop.” If she said that after seeing the results of one of these studies, which scenario was she probably looking at?

A. Scenario A

B. Scenario B

C. Scenario C

D. None of the above

10.

The scenarios below are possible results of a study in which participants completed a measure of how important religion was to them personally. Participants are either from a Rural or Urban area, and are either Poor or Rich.

A sociologist said, “As far as how important religion is to people, it doesn’t matter where they live. What matters is how much money they make.” If this conclusion was based on one of these scenarios, which scenario was being considered?

A. Scenario A

B. Scenario B

C. Scenario C

D. None of the above

11.

All of the following are advantages of factorial designs EXCEPT:

A. they automatically provide an indicator of effect size for the measured variable.

B. they are more efficient.

C. the combined influences of variables can be studied.

D. more than one grouping variable can be considered in the same study.

12.

The scenarios below are possible results of a study in which participants completed a measure of how important religion was to them personally. Participants are either from a Rural or Urban area, and are either Poor or Rich.

Which statement is true about Scenario B?

A. There is a moderate interaction effect.

B.

Religion is consistently more important for rich people than for poor

people, regardless of where they live.

C.

Religion is more important to people who live in the urban areas,

regardless of their wealth.

D.

Religion is particularly important to people who are both poor and live

in rural areas.

13.

For a factorial analysis of variance, the assumptions that were necessary for a one-way analysis of variance:

A. are no longer required.

B. are necessary for each cell.

C. are unchanged.

D. are unchanged, but less important, because factorial analysis of variance is more robust than one-way analysis of variance.

14.

How many F ratios are figured in a two-way analysis of variance?

A. 1

B. 2

C. 3

D. as many as there are cells in the design

15.

When drawing a regression line for a linear prediction rule, the minimum number of predicted points on a graph that must be located is:

A. 1.

B. 2.

C. 1 if it is a positively sloped line; 2 if it is a negatively sloped line.

D. 2 if it is a positively sloped line; 1 if it is a negatively sloped line.

16.

In the equation Ŷ = a + (b)(X), b is the symbol for the:

A. correlation coefficient.

B. regression coefficient.

C. proportionate reduction in error.

D. regression constant.

17.

Which of the following calculations is necessary for figuring the correlation coefficient?

A. Finding the grand mean

B. Finding the cross-products of each person’s X and Y raw scores

C. Finding the means of X and Y

D. Finding the difference between each person’s X and Y raw scores

18.

In a bivariate linear prediction, the null hypothesis is that:

A. β = 0.

B. β = 1.

C. β ≠ 0.

D. β ≠ 1.

19.

In a linear prediction rule using a standardized regression coefficient:

A. the regression constant is always equal to 1.

B. for each increase of one standard deviation in the predictor variable, the predicted standard deviation of the criterion variable increases by the standardized regression coefficient.

C. the predicted value for the criterion variable is a t score.

D. for each increase of one standard deviation in the predicted variable, the predicted standard deviation of the predictor variable increases by the standardized regression coefficient.

20.

What is the direction of causality when two variables, A and B, have a strong linear correlation?

A. A causes B

B. B causes A

C. Some third variable is causing both A and B

D. All of the above are possible

21.

When the relationship between two variables is shown by listing the variables on both the top and left side, the table is called a:

A. correlation matrix.

B. scatter diagram.

C. binomial effect size display.

D. C table.

22.

When conducting a t test for the correlation coefficient in a study with 16 individuals, the degrees of freedom will be:

A. 14

B. 15

C. 30

D. 31

23.

Error in regression is figured by:

A. Y – X.

B. Y – Ŷ.

C. Y – b.

D. Y – a.

24.

When figuring a correlation coefficient, an outlier:

A. usually has only a small effect on the computed correlation.

B. can have a strong effect on the computed correlation.

C. generally increases the statistical power of the study.

D. can be balanced by the effects of attenuation.

25.

The BEST linear prediction rule is the one that has the least:

A. error when predicting from the mean.

B. squared error when predicting from the mean.

C. error when predicting using that rule.

D. squared error when predicting using that rule.

26.

Which of the following is true about hypothesis testing for a linear prediction rule?

A. If the correlation coefficient is significant, the regression coefficient will be significant.

B. If the correlation coefficient is significant, the standardized regression coefficient will be significant, but the unstandardized (ordinary) regression coefficient will not.

C. The t test for the correlation coefficient tests the significance of the regression constant.

D. The t test for the correlation coefficient tests the significance of both the regression constant and the regression coefficient

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