Question 1

Use the following statistics to determine the statistical significance of the regression:

Accepted Answer

A)  ANOVA Sig. 
B)  R2 Linear value 
C)  Unstandardized Coefficient 
D)  Standard Error of the Estimate 
A)  ANOVA Sig. 
B)  R2 Linear value 
C)  Unstandardized Coefficient 
D)  Standard Error of the Estimate A

Question 2

Linear regression requires two variables at the ordinal level.

Accepted Answer

A) True 
 B)False  False

Question 3

The ANOVA output box contains the coefficient of determination.

Accepted Answer

A) True 
 B)False  False

Question 4

A significance value of less than .05 indicates a statistically significant finding for an alpha-level of 5%.

Accepted Answer

A) True 
 B)False

Question 5

The SPSS Statistics tool labels the variables used in linear regression as independent and dependent.

Accepted Answer

A) True 
 B)False

Question 6

Use the following SPSS Statistics tool to edit graphs:

Accepted Answer

A)  Chart Builder 
B)  Descriptive Statistics 
C)  Graph Editor 
D)  Chart Editor 
A)  Chart Builder 
B)  Descriptive Statistics 
C)  Graph Editor 
D)  Chart Editor

Question 7

Linear regression involves predicting the outcome of one variable (dependent) based on the input of another variable (independent).

Accepted Answer

A) True 
 B)False

Question 8

SPSS Statistics calculates the following outputs for a linear regression analysis:

Accepted Answer

A)  Model Summary 
B)  ANOVA 
C)  Coefficients 
D)  All of the above 
A)  Model Summary 
B)  ANOVA 
C)  Coefficients 
D)  All of the above

Question 9

The following statistics can be displayed on the scattergram:

Accepted Answer

A)  Regression equation 
B)  R2 Linear value 
C)  Data points 
D)  All of the above 
A)  Regression equation 
B)  R2 Linear value 
C)  Data points 
D)  All of the above

Question 10

Linear regression is a statistical method requiring the following variable types:

Accepted Answer

A)  Two variables at the ordinal level. 
B)  One variable at the ordinal level and one at the scale level. 
C)  Two variables at the scale level. 
D)  None of the above. 
A)  Two variables at the ordinal level. 
B)  One variable at the ordinal level and one at the scale level. 
C)  Two variables at the scale level. 
D)  None of the above.

Use the following statistics to determine the statistical significance of the regression:

Linear regression requires two variables at the ordinal level.

The ANOVA output box contains the coefficient of determination.

A significance value of less than .05 indicates a statistically significant finding for an alpha-level of 5%.

The SPSS Statistics tool labels the variables used in linear regression as independent and dependent.

Use the following SPSS Statistics tool to edit graphs:

Linear regression involves predicting the outcome of one variable (dependent) based on the input of another variable (independent).

SPSS Statistics calculates the following outputs for a linear regression analysis:

The following statistics can be displayed on the scattergram:

Linear regression is a statistical method requiring the following variable types:

Levels of Measurement in SPSS

Entering and Saving a Set of Scores Scale Variable

Frequency Distribution

Histogram

Frequency Polygon

Mean, Median, and Mode: One Group, Two Scale Variables

Mean and Standard Deviation: Two or More Groups, One Scale Variable

Z-Scores Standard Scores

Scattergram

Correlation Coefficients: The Pearson R and Spearmans RHO

The T-Test for a Single Sample Mean

Paired-Samples T-Test

Independent-Samples T-Test

One-Way ANOVA

Chi-Square Goodness-Of-Fit Test

Chi-Square Test of Independence

Filters

Exam 11: Simple Linear Regression

Use the following statistics to determine the statistical significance of the regression:

Linear regression requires two variables at the ordinal level.

The ANOVA output box contains the coefficient of determination.

A significance value of less than .05 indicates a statistically significant finding for an alpha-level of 5%.

The SPSS Statistics tool labels the variables used in linear regression as independent and dependent.

Use the following SPSS Statistics tool to edit graphs:

Linear regression involves predicting the outcome of one variable (dependent) based on the input of another variable (independent).

SPSS Statistics calculates the following outputs for a linear regression analysis:

The following statistics can be displayed on the scattergram:

Linear regression is a statistical method requiring the following variable types:

Levels of Measurement in SPSS

Entering and Saving a Set of Scores Scale Variable

Frequency Distribution

Histogram

Frequency Polygon

Mean, Median, and Mode: One Group, Two Scale Variables

Mean and Standard Deviation: Two or More Groups, One Scale Variable

Z-Scores Standard Scores

Scattergram

Correlation Coefficients: The Pearson R and Spearmans RHO

The T-Test for a Single Sample Mean

Paired-Samples T-Test

Independent-Samples T-Test

One-Way ANOVA

Chi-Square Goodness-Of-Fit Test

Chi-Square Test of Independence

Filters