Question 1

What do between-groups variance and within-groups variance include?

Accepted Answer

The between-groups variance includes systematic variance (the effects of the independent variable and possibly confounds) and error variance. The within-groups variance includes variance due to chance factors.

Question 2

If the null hypothesis for an ANOVA is false, then the F-ratio should be:

Accepted Answer

A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less. 
A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less. C

Question 3

If between-groups variance is large, then we have likely observed:

Accepted Answer

A)  experimenter effects. 
B)  an effect of the dependent variable. 
C)  enough samples. 
D)  an effect of the independent variable. 
A)  experimenter effects. 
B)  an effect of the dependent variable. 
C)  enough samples. 
D)  an effect of the independent variable. D

Question 4

What is the Bonferroni adjustment? What would the Bonferoni adjustment be for a study with four groups for which a researcher decided to use t tests for comparisons with $\alpha$ = .05?

Accepted Answer

The Bonferroni adjustment is a means of

Question 5

The Bonferroni adjustment for a study in which I had three groups I wanted to compare would be:

Accepted Answer

A)  .01. 
B)  .014. 
C)  .017. 
D)  .020. 
A)  .01. 
B)  .014. 
C)  .017. 
D)  .020.

Question 6

The smaller the between-groups variance, _____.

Accepted Answer

A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the easier it becomes to show a causal effect of the independent variable on the dependent variable 
A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the easier it becomes to show a causal effect of the independent variable on the dependent variable

Question 7

When the F-ratio is larger than 1.00, it means that:

Accepted Answer

A)  a mistake has been made in the computation. 
B)  there are large error effects present. 
C)  the experimental manipulation probably had the predicted effects. 
D)  the between-groups variation is no larger than would be expected by chance alone and no larger than the within-groups variance. 
A)  a mistake has been made in the computation. 
B)  there are large error effects present. 
C)  the experimental manipulation probably had the predicted effects. 
D)  the between-groups variation is no larger than would be expected by chance alone and no larger than the within-groups variance.

Question 8

The larger the between-groups variance, _____.

Accepted Answer

A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the smaller the final F-ratio 
A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the smaller the final F-ratio

Question 9

If I used four t tests to make comparisons between four groups on which I had collected data, the probability of a Type I error would be:

Accepted Answer

A)  .05. 
B)  .01. 
C)  .14. 
D)  .19. 
A)  .05. 
B)  .01. 
C)  .14. 
D)  .19.

Question 10

If within-groups variance is large, then we have observed:

Accepted Answer

A)  experimenter effects. 
B)  an effect of the dependent variable. 
C)  a large amount of error variance. 
D)  an effect of the independent variable. 
A)  experimenter effects. 
B)  an effect of the dependent variable. 
C)  a large amount of error variance. 
D)  an effect of the independent variable.

Question 11

If the null hypothesis for an ANOVA is true, then the F-ratio should be:

Accepted Answer

A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less. 
A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less.

Question 12

To determine the probability of a Type I error when using multiple comparisons, we use the following formula:

Accepted Answer

A)  1- (1 - .05)c. 
B)  1- (1 - .95)c.
c 1- (.95 - .05)c.
d. 1- (1 - .01)c. 
A)  1- (1 - .05)c. 
B)  1- (1 - .95)c.
c 1- (.95 - .05)c.
d. 1- (1 - .01)c.

Question 13

If the alternative hypothesis for an ANOVA is supported, then the F-ratio should be:

Accepted Answer

A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less. 
A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less.

Question 14

The alternative hypothesis for a one-way randomized ANOVA states that:

Accepted Answer

A)  H0: $\mu$1 = $\mu$2 = $\mu$3. 
B)  H0: $\mu$1 $\not =$ $\mu$2 $\not =$ $\mu$3.  
C)  Ha: $\mu$1 = $\mu$2 = $\mu$3.  
D)  Ha: at least one $\mu$ differs from the others. 
A)  H0: $\mu$1 = $\mu$2 = $\mu$3. 
B)  H0: $\mu$1 $\not =$ $\mu$2 $\not =$ $\mu$3.  
C)  Ha: $\mu$1 = $\mu$2 = $\mu$3.  
D)  Ha: at least one $\mu$ differs from the others.

Question 15

If the alternative hypothesis for an ANOVA is not supported, then the F-ratio should be:

Accepted Answer

A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less. 
A)  greater than 5.00. 
B)  a negative number. 
C)  greater than 1.00. 
D)  1.00 or less.

Question 16

If I used three t tests to make comparisons between three groups on which I had collected data, the probability of a Type I error would be:

Accepted Answer

A)  .05. 
B)  .01. 
C)  .14. 
D)  .22. 
A)  .05. 
B)  .01. 
C)  .14. 
D)  .22.

Question 17

The null hypothesis for a one-way randomized ANOVA states that:

Accepted Answer

A)  H0: $\mu$1 =  $\mu$2 =  $\mu$3. 
B)  H0:  $\mu$1 $\not =$  $\mu$2 $\not =$ $\mu$3.  
C)  Ha:  $\mu$1 =  $\mu$2 =  $\mu$3.  
D)  Ha:  $\mu$1 $\not =$  $\mu$2 $\not =$  $\mu$3. 
A)  H0: $\mu$1 =  $\mu$2 =  $\mu$3. 
B)  H0:  $\mu$1 $\not =$  $\mu$2 $\not =$ $\mu$3.  
C)  Ha:  $\mu$1 =  $\mu$2 =  $\mu$3.  
D)  Ha:  $\mu$1 $\not =$  $\mu$2 $\not =$  $\mu$3.

Question 18

The Bonferroni adjustment for a study in which I had four groups I wanted to compare would be:

Accepted Answer

A)  .01. 
B)  .017. 
C)  .0125. 
D)  .0225. 
A)  .01. 
B)  .017. 
C)  .0125. 
D)  .0225.

Question 19

The smaller the within-groups (error) variance, _____.

Accepted Answer

A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the easier it becomes to show a causal effect of the dependent variable on the independent variable 
A)  the more difficult it becomes to show the effects of experimental variance 
B)  the easier it becomes to show the effects of experimental variance 
C)  the more difficult it becomes to perform the F test 
D)  the easier it becomes to show a causal effect of the dependent variable on the independent variable

What do between-groups variance and within-groups variance include?

If the null hypothesis for an ANOVA is false, then the F-ratio should be:

If between-groups variance is large, then we have likely observed:

What is the Bonferroni adjustment? What would the Bonferoni adjustment be for a study with four groups for which a researcher decided to use t tests for comparisons with $\alpha$ = .05?

The Bonferroni adjustment for a study in which I had three groups I wanted to compare would be:

The smaller the between-groups variance, _____.

When the F-ratio is larger than 1.00, it means that:

The larger the between-groups variance, _____.

If I used four t tests to make comparisons between four groups on which I had collected data, the probability of a Type I error would be:

If within-groups variance is large, then we have observed:

If the null hypothesis for an ANOVA is true, then the F-ratio should be:

To determine the probability of a Type I error when using multiple comparisons, we use the following formula:

If the alternative hypothesis for an ANOVA is supported, then the F-ratio should be:

The alternative hypothesis for a one-way randomized ANOVA states that:

If the alternative hypothesis for an ANOVA is not supported, then the F-ratio should be:

If I used three t tests to make comparisons between three groups on which I had collected data, the probability of a Type I error would be:

The null hypothesis for a one-way randomized ANOVA states that:

The Bonferroni adjustment for a study in which I had four groups I wanted to compare would be:

The smaller the within-groups (error) variance, _____.

Science and Statistics

Organizing Data, Variables and Measurement

Measures of Central Tendency

Measures of Variation

Standard Scores Z Scores

Probability, Hypothesis Testing and Inferential Statistics

The Single-Sample Z Test

The Single-Sample T Test

The T Test for Independent Groups Samples

T Test for Correlated Groups Samples

One-Way Between-Subjects Analysis of Variance Anova

One-Way Repeated Measures Anova

Using Designs With More Than One Independent Variable and Two-Way Between-Subjects Anova

Correlational Research and Correlation Coefficients

Advanced Correlational Techniques: Regression Analysis

Chi-Square Tests

Tests for Ordinal Data

Filters

Exam 11: Comparing More Than Two Groups

What do between-groups variance and within-groups variance include?

If the null hypothesis for an ANOVA is false, then the F-ratio should be:

If between-groups variance is large, then we have likely observed:

What is the Bonferroni adjustment? What would the Bonferoni adjustment be for a study with four groups for which a researcher decided to use t tests for comparisons with α\alphaα = .05?

The Bonferroni adjustment for a study in which I had three groups I wanted to compare would be:

The smaller the between-groups variance, _____.

When the F-ratio is larger than 1.00, it means that:

The larger the between-groups variance, _____.

If I used four t tests to make comparisons between four groups on which I had collected data, the probability of a Type I error would be:

If within-groups variance is large, then we have observed:

If the null hypothesis for an ANOVA is true, then the F-ratio should be:

To determine the probability of a Type I error when using multiple comparisons, we use the following formula:

If the alternative hypothesis for an ANOVA is supported, then the F-ratio should be:

The alternative hypothesis for a one-way randomized ANOVA states that:

If the alternative hypothesis for an ANOVA is not supported, then the F-ratio should be:

If I used three t tests to make comparisons between three groups on which I had collected data, the probability of a Type I error would be:

The null hypothesis for a one-way randomized ANOVA states that:

The Bonferroni adjustment for a study in which I had four groups I wanted to compare would be:

The smaller the within-groups (error) variance, _____.

Science and Statistics

Organizing Data, Variables and Measurement

Measures of Central Tendency

Measures of Variation

Standard Scores Z Scores

Probability, Hypothesis Testing and Inferential Statistics

The Single-Sample Z Test

The Single-Sample T Test

The T Test for Independent Groups Samples

T Test for Correlated Groups Samples

One-Way Between-Subjects Analysis of Variance Anova

One-Way Repeated Measures Anova

Using Designs With More Than One Independent Variable and Two-Way Between-Subjects Anova

Correlational Research and Correlation Coefficients

Advanced Correlational Techniques: Regression Analysis

Chi-Square Tests

Tests for Ordinal Data

Filters

What is the Bonferroni adjustment? What would the Bonferoni adjustment be for a study with four groups for which a researcher decided to use t tests for comparisons with $\alpha$ = .05?