Question 1

__________ are designed to control the experimentwise alpha level in means comparisons that are made after the data have been collected.

Accepted Answer

Post hoc means comparisons are specifically designed to control the experimentwise alpha level when making multiple comparisons after the data have been collected, to ensure that the overall chance of making a Type I error is managed.

Question 2

Which of the following can be used to control for the effects of potential confounding variables?

Accepted Answer

Multiple regression can be used to control for the effects of potential confounding variables by including them as covariates in the analysis, allowing for the isolation of the effect of the primary independent variable(s) of interest.

Question 3

Means that are not being compared in a contrast analysis are given the contrast weight of

Accepted Answer

In contrast analysis, means that are not being compared (i.e., not of interest in the specific contrast being tested) are given a contrast weight of zero. This effectively removes them from the calculation of that particular contrast.

Question 4

The effect size statistic for a multiple regression is

Accepted Answer

The effect size statistic for a multiple regression is R, which represents the correlation between the predicted values and the observed values.

Question 5

Which of the following means comparison analyses involves comparing the F comparison to a critical F value that is adjusted to take into consideration the number of possible comparisons?

Accepted Answer

The Scheffé means comparison test involves comparing the F comparison to a critical F value that is adjusted to take into consideration the number of possible comparisons. This method is particularly useful when the researcher wants to conduct multiple post-hoc comparisons among group means after an ANOVA test, as it controls the overall Type I error rate across all comparisons.

Question 6

According to the multiple regression equation, the best prediction of the outcome variable (Ŷ) is equal to

Accepted Answer

The best prediction of the outcome variable (Ŷ) in a multiple regression equation is equal to the intercept plus the sum of all the predictor variables (X's), each multiplied by their respective regression coefficients. This accounts for the baseline value (intercept) and the weighted contribution of each predictor.

Question 7

In a multiple regression analysis, which of the following represents the linear relationship between each predictor variable and the outcome variable, controlling for each of the other predictor variables?

Accepted Answer

The regression coefficient in a multiple regression analysis represents the linear relationship between each predictor variable and the outcome variable, controlling for the other predictor variables. It indicates how much the dependent variable is expected to increase (or decrease) when that predictor variable increases by one unit, holding all other predictors constant.

Question 8

A __________ analysis is a statistical procedure that is used when more than one nominal variable is used to predict a nominal outcome variable.

Accepted Answer

Loglinear analysis is used when more than one nominal variable is used to predict a nominal outcome variable, making it suitable for examining the relationships between categorical variables.

Question 9

A contrast analysis involves

Accepted Answer

A contrast analysis involves computing an F value, which is used to determine whether there are statistically significant differences between group means in various types of analysis of variance (ANOVA) tests.

Question 10

In a multiple regression, R squared indicates

Accepted Answer

R squared in a multiple regression model represents the proportion of the variance in the dependent (outcome) variable that can be explained by the independent (predictor) variables. It is a measure of how well the model fits the data.

Question 11

Which of the following refers to a multiple regression analysis in which all of the predictor variables are entered in at the same time in order to predict the outcome variable?

Accepted Answer

Simultaneous multiple regression involves entering all predictor variables into the regression model at the same time to predict the outcome variable. This approach contrasts with hierarchical and stepwise methods, where variables are entered into the model in steps based on theoretical considerations or statistical criteria. Covariance multiple regression is not a recognized term in the context of regression analysis methodologies.

Question 12

A researcher has developed a theory about which predictor variable should be entered first, second, and third to predict the outcome variable. He will want to use which of the following?

Accepted Answer

Hierarchical multiple regression is used when a researcher has a specific hypothesis about the order in which predictor variables should be entered into the regression equation. This method allows the researcher to control the order of entry of variables based on theoretical or empirical justifications.

Question 13

A means comparison is used

Accepted Answer

Means comparison is primarily used to test the differences between and among particular group means, allowing researchers to understand if there are significant differences in the average outcomes across different groups.

Question 14

In a multiple regression analysis, the __________ indicates the extent to which the predictor variables as a group predict the outcome variable.

Accepted Answer

The multiple correlation coefficient (often denoted as R or R^2 in the context of multiple regression) indicates the extent to which the predictor variables as a group predict the outcome variable. It represents the strength and direction of the linear relationship between the predictors and the outcome.

Question 15

In a contrast analysis, the sum of the contrast weights

Accepted Answer

The sum of the contrast weights in a contrast analysis must equal zero. This is because contrast analysis is used to compare means and the weights are assigned to reflect the comparison being made, with the requirement that the sum of these weights equals zero to ensure that the comparison is balanced.

Question 16

What is the most general method of conducting means comparisons that have been planned a priori?

Accepted Answer

Contrast analysis is the most general method for conducting means comparisons that have been planned before the data were collected (a priori). It allows for specific hypotheses about group means to be tested directly.

Question 17

Which of the following is NOT a use of multiple regression analysis?

Accepted Answer

The answer of Which of the following is NOT a...

Question 18

Which of the following procedures protects against increases in the experimentwise alpha by only allowing post hoc comparisons if the initial ANOVA F value is significant?

Accepted Answer

The Fisher least significant difference test is a post hoc test that is only conducted if the initial ANOVA F test is significant, thus controlling the experimentwise alpha level by not performing unnecessary comparisons.

Question 19

Which of the following refers to a multiple regression analysis in which the predictor variables that produce the biggest increase in the multiple R are entered first?

Accepted Answer

Stepwise multiple regression is a method where predictor variables are added to the regression model one at a time based on statistical criteria, typically starting with the variable that has the strongest correlation with the dependent variable, thus producing the biggest increase in the multiple R.

Question 20

Contrast weights are set by the researchers in order to

Accepted Answer

Contrast weights are specifically set by researchers to indicate how the group means are to be compared. This allows for specific hypotheses about the differences between group means to be tested.

Quiz 18: Multivariate Statistics