Question 1

In experimental studies, IVs may also be referred to as criterion or outcome variables.

Accepted Answer

A) True 
 B)False

Question 2

Bivariate statistics refers to analyses that involve two variables where one is identified as an IV and the other is identified as a DV.

Accepted Answer

A) True 
 B)False

Question 3

Measures of variability include:

Accepted Answer

A)  Range, quartile deviation, and standard deviation. 
B)  Only standard deviation and variance. 
C)  Range, standard deviation, and mean. 
D)  Standard deviation, mean, and variance. 
A)  Range, quartile deviation, and standard deviation. 
B)  Only standard deviation and variance. 
C)  Range, standard deviation, and mean. 
D)  Standard deviation, mean, and variance.

Question 4

In nonexperimental research (e.g., descriptive, correlational, survey, or causal-comparative designs), the researcher has no control over the levels of the independent variables (IVs).

Accepted Answer

A) True 
 B)False

Question 5

When variables are correlated, they have overlapping, or shared, variance.

Accepted Answer

A) True 
 B)False

Question 6

In experimental studies, DVs are sometimes referred to as the predictor or causal variables.

Accepted Answer

A) True 
 B)False

Question 7

Orthogonality is perfect association between variables.

Accepted Answer

A) True 
 B)False

Question 8

The basic distinction between experimental and nonexperimental research designs is whether the levels of the independent variable(s) have been manipulated by the researcher.

Accepted Answer

A) True 
 B)False

Question 9

Univariate statistics refers to analyses where there is only one IV and one DV.

Accepted Answer

A) True 
 B)False

Question 10

The two most common measures of relative position are:

Accepted Answer

A)  Mean and standard deviation. 
B)  Percentile ranks and standard scores. 
C)  z-scores and T-scores. 
D)  Spearman rho and Pearson r. 
A)  Mean and standard deviation. 
B)  Percentile ranks and standard scores. 
C)  z-scores and T-scores. 
D)  Spearman rho and Pearson r.

In experimental studies, IVs may also be referred to as criterion or outcome variables.

Bivariate statistics refers to analyses that involve two variables where one is identified as an IV and the other is identified as a DV.

Measures of variability include:

In nonexperimental research (e.g., descriptive, correlational, survey, or causal-comparative designs), the researcher has no control over the levels of the independent variables (IVs).

When variables are correlated, they have overlapping, or shared, variance.

In experimental studies, DVs are sometimes referred to as the predictor or causal variables.

Orthogonality is perfect association between variables.

The basic distinction between experimental and nonexperimental research designs is whether the levels of the independent variable(s) have been manipulated by the researcher.

Univariate statistics refers to analyses where there is only one IV and one DV.

The two most common measures of relative position are:

A Guide to Multivariate Techniques

Pre-Analysis Data Screening

Factorial Analysis of Variance

Analysis of Covariance

Multivariate Analysis of Variance and Covariance

Multiple Regression

Path Analysis

Factor Analysis

Discriminant Analysis

Logistic Regression

Filters

Exam 1: Introduction to Multivariate Statistics

In experimental studies, IVs may also be referred to as criterion or outcome variables.

Bivariate statistics refers to analyses that involve two variables where one is identified as an IV and the other is identified as a DV.

Measures of variability include:

In nonexperimental research (e.g., descriptive, correlational, survey, or causal-comparative designs), the researcher has no control over the levels of the independent variables (IVs).

When variables are correlated, they have overlapping, or shared, variance.

In experimental studies, DVs are sometimes referred to as the predictor or causal variables.

Orthogonality is perfect association between variables.

The basic distinction between experimental and nonexperimental research designs is whether the levels of the independent variable(s) have been manipulated by the researcher.

Univariate statistics refers to analyses where there is only one IV and one DV.

The two most common measures of relative position are:

A Guide to Multivariate Techniques

Pre-Analysis Data Screening

Factorial Analysis of Variance

Analysis of Covariance

Multivariate Analysis of Variance and Covariance

Multiple Regression

Path Analysis

Factor Analysis

Discriminant Analysis

Logistic Regression

Filters