Analysis of Variance

Definitions

100

T test

What is the name of the test that is used in studies to compare the means of two sets of data.

200

The F table (distribution) is a right-skewed distribution used most commonly in Analysis of Variance. When referencing the F distribution, the numerator degrees of freedom are always given first, as switching the order of degrees of freedom changes the distribution (e.g., F(10,12) does not equal F(12,10) ).

What is an f table?

300

post hoc test

What test is described here: tests that are run to confirm where the differences occurred between groups, they should only be run when you have a shown an overall significant difference in group means (i.e., a significant one-way ANOVA result).

400

The One-Way Analysis

what is a technique used to compare means of two or more samples and can only use numerical data?

500

Analysis of Variance

What does ANOVA stand for?

True/False

100

false

It is important to use the post hoc test during the experiment.

200

false. It can also be used to compare three or more groups simultaneously.

The One-Way Analysis of variance can only be used to compare two groups.

300

true

The t test is commonly used but does has two main limitations such as: 1. Can only test differences between 2 groups 2. Limited to single group OR repeated measures designs

400

true.

Analysis of Variance designs with multiple independent variables are referred to as factorial designs.

500

false.

Use of ANOVA involves three assumptions about the populations from which samples are drawn:1. that populations are randomly distributed. 2. that there is heterogeneity of variance among the groups, and 3. that the observations are dependent.

Multiple Choice

100

b.

What is the "One-Way design" a) design where subjects are randomly assigned to groups. b) study where there is only one independent variable. c) An independent variable d) factors that are randomly selected.

200

c.

What is the One-Way Analysis used for? a) to test multiple groups on multiple factors. b) to test a single group on multiple factors. c) to test multiple groups on only one factor.

300

a,b,c,d are all correct

Manipulated variables are controlled by the researcher in which of the following (select all that apply). a) the researcher controls who gets it by random assignment. b) the researcher controls the exact nature of the independent variables c) the researcher controls exactly when the variable is to occur. d) the researcher controls the exact duration of the independent variable.

400

b.

What is the best way for the researcher to minimize heterogeneity of variance? a) to ensure that there is inconsistency in the groups. b) to ensure that there is consistency in the groups. c) to ensure that there is diversity in the groups. d) to ensure that there is multiple variables in the groups.

500

a,b,d

Which of the following are true concerning ANOVA testing? (circle all that apply) a) ANOVA detects differences among multiple groups b) ANOVA analyzes the differences between group means and their associated procedures c) When using ANOVA, you do not need to use any other test because it is sufficiently accurate. d) ANOVA stands for Analysis of Variance.

Short Answer

100

A t-test is used for testing the mean of one population. An F-test is used to compare 2 populations’ variances.

What is the difference between the t test and the F test?

200

No.

Can I use the t test to compare multiple groups?

300

Yes. By using ANOVA rather than simple t-tests.

Can I test for how two different variables interact with each other?

400

In statistics, the mean squared error (MSE) of an estimator measures the average of the squares of the "errors", that is, the difference between the estimator and what is estimated.

What is a mean square?

500

ANOVA test tells you whether you have an overall difference between your groups, but it does not tell you which specific groups differed - post hoc tests do. Because post hoc tests are run to confirm where the differences occurred between groups, they should only be run when you have a shown an overall significant difference in group means (i.e., a significant one-way ANOVA result).

Why would you use a post hoc test?