Question 1

Another purpose for screening data is to enter missing data and assess the effect of and ways to deal with complete data.

Accepted Answer

A) True 
 B)False  False

Question 2

Multivariate outliers are cases with unusual combinations of scores on two or more variables.

Accepted Answer

A) True 
 B)False  True

Question 3

Pre-analysis data screening is an analysis after the analysis.

Accepted Answer

A) True 
 B)False  False

Question 4

Skewness is a quantitative measure of the degree of peakedness of a distribution.

Accepted Answer

A) True 
 B)False

Question 5

In multivariate situations, homoscedasticity can be assessed statistically by using Box's M test for equality of variance-covariance matrices.

Accepted Answer

A) True 
 B)False

Question 6

One of the fundamental causes for outliers is that data-entry errors were made by the research participant.

Accepted Answer

A) True 
 B)False

Question 7

The main purpose for screening data prior to conducting a multivariate analysis is to deal with the accuracy of the findings.

Accepted Answer

A) True 
 B)False

Question 8

A third alternative for handling missing data deletes the missing values using a regression approach.

Accepted Answer

A) True 
 B)False

Question 9

Linearity presupposes that:

Accepted Answer

A)  There is a straight-line relationship between two variables. 
B)  The variability in scores for one continuous variable is roughly the same at all values. of another continuous variable. 
C)  Both (a) and (b) are correct. 
D)  Neither (a) nor (b) is correct. 
A)  There is a straight-line relationship between two variables. 
B)  The variability in scores for one continuous variable is roughly the same at all values. of another continuous variable. 
C)  Both (a) and (b) are correct. 
D)  Neither (a) nor (b) is correct.

Question 10

Many researchers tend to assume that any missing data that occur within their dataset:

Accepted Answer

A)  Are random in nature. 
B)  Are caused by research participants not giving honest answers. 
C)  Reflect responses to a taboo topic where participants were ashamed to answer the question(s). 
D)  None of the above is correct. 
A)  Are random in nature. 
B)  Are caused by research participants not giving honest answers. 
C)  Reflect responses to a taboo topic where participants were ashamed to answer the question(s). 
D)  None of the above is correct.

Question 11

If a researcher decides that the missing data are important and need to be addressed, the first thing to do is to estimate the missing values and then use these values during the main analysis.

Accepted Answer

A) True 
 B)False

Question 12

A third purpose of screening data is to assess the effects of large values on either end of the distribution.

Accepted Answer

A) True 
 B)False

Question 13

There are three fundamental causes for outliers:

Accepted Answer

A)  Data-entry errors were made by the researcher. 
B)  The participant is not a member of the population for which the sample is intended. 
C)  The participant is simply different from the remainder of the sample. 
D)  All three are correct. 
A)  Data-entry errors were made by the researcher. 
B)  The participant is not a member of the population for which the sample is intended. 
C)  The participant is simply different from the remainder of the sample. 
D)  All three are correct.

Question 14

A fourth purpose of screening data is to assess the adequacy of fit between the data and to make assumptions of a specific procedure.

Accepted Answer

A) True 
 B)False

Question 15

With univariate analyses, homogeneity of variances is assessed statistically with Levene's test.

Accepted Answer

A) True 
 B)False

Question 16

Kurtosis is a quantitative measure of the degree of symmetry of a distribution about the mean.

Accepted Answer

A) True 
 B)False

Question 17

Linearity presupposes that there is a straight-line relationship between two variables.

Accepted Answer

A) True 
 B)False

Question 18

The best thing to do when a data set includes missing data is to collect new data.

Accepted Answer

A) True 
 B)False

Question 19

The Kolmogorov-Smirnov statistic tests the null hypothesis that the variables in the population are linear.

Accepted Answer

A) True 
 B)False

Question 20

There are three general assumptions involved in multivariate statistical testing:

Accepted Answer

A)  Normality. 
B)  Linearity. 
C)  Homoscedasticity. 
D)  All three are correct. 
A)  Normality. 
B)  Linearity. 
C)  Homoscedasticity. 
D)  All three are correct.

Another purpose for screening data is to enter missing data and assess the effect of and ways to deal with complete data.

Multivariate outliers are cases with unusual combinations of scores on two or more variables.

Pre-analysis data screening is an analysis after the analysis.

Skewness is a quantitative measure of the degree of peakedness of a distribution.

In multivariate situations, homoscedasticity can be assessed statistically by using Box's M test for equality of variance-covariance matrices.

One of the fundamental causes for outliers is that data-entry errors were made by the research participant.

The main purpose for screening data prior to conducting a multivariate analysis is to deal with the accuracy of the findings.

A third alternative for handling missing data deletes the missing values using a regression approach.

Linearity presupposes that:

Many researchers tend to assume that any missing data that occur within their dataset:

If a researcher decides that the missing data are important and need to be addressed, the first thing to do is to estimate the missing values and then use these values during the main analysis.

A third purpose of screening data is to assess the effects of large values on either end of the distribution.

There are three fundamental causes for outliers:

A fourth purpose of screening data is to assess the adequacy of fit between the data and to make assumptions of a specific procedure.

With univariate analyses, homogeneity of variances is assessed statistically with Levene's test.

Kurtosis is a quantitative measure of the degree of symmetry of a distribution about the mean.

Linearity presupposes that there is a straight-line relationship between two variables.

The best thing to do when a data set includes missing data is to collect new data.

The Kolmogorov-Smirnov statistic tests the null hypothesis that the variables in the population are linear.

There are three general assumptions involved in multivariate statistical testing:

Introduction to Multivariate Statistics

A Guide to Multivariate Techniques

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 3: Pre-Analysis Data Screening

Another purpose for screening data is to enter missing data and assess the effect of and ways to deal with complete data.

Multivariate outliers are cases with unusual combinations of scores on two or more variables.

Pre-analysis data screening is an analysis after the analysis.

Skewness is a quantitative measure of the degree of peakedness of a distribution.

In multivariate situations, homoscedasticity can be assessed statistically by using Box's M test for equality of variance-covariance matrices.

One of the fundamental causes for outliers is that data-entry errors were made by the research participant.

The main purpose for screening data prior to conducting a multivariate analysis is to deal with the accuracy of the findings.

A third alternative for handling missing data deletes the missing values using a regression approach.

Linearity presupposes that:

Many researchers tend to assume that any missing data that occur within their dataset:

If a researcher decides that the missing data are important and need to be addressed, the first thing to do is to estimate the missing values and then use these values during the main analysis.

A third purpose of screening data is to assess the effects of large values on either end of the distribution.

There are three fundamental causes for outliers:

A fourth purpose of screening data is to assess the adequacy of fit between the data and to make assumptions of a specific procedure.

With univariate analyses, homogeneity of variances is assessed statistically with Levene's test.

Kurtosis is a quantitative measure of the degree of symmetry of a distribution about the mean.

Linearity presupposes that there is a straight-line relationship between two variables.

The best thing to do when a data set includes missing data is to collect new data.

The Kolmogorov-Smirnov statistic tests the null hypothesis that the variables in the population are linear.

There are three general assumptions involved in multivariate statistical testing:

Introduction to Multivariate Statistics

A Guide to Multivariate Techniques

Factorial Analysis of Variance

Analysis of Covariance

Multivariate Analysis of Variance and Covariance

Multiple Regression

Path Analysis

Factor Analysis

Discriminant Analysis

Logistic Regression

Filters