A1B2C3!

Factorial A

100

A factorial design includes multiple ______ in a single study.

factors/independent variables

200

The interaction tests whether the effect of one factor ______ the level of the other factor.

Depends on

300

We are conducting a 3x4 factorial ANOVA. How many independent variables do we have?

2

400

The requirement that the score from different participants within each sample to be ______ is an example of one of the test assumptions for the two-way between-subjects ANOVA test.

independent

500

This is the means for each level of an independent variable in a factorial design.

Marginal Means

Within-Subjects

100

In ______ designs, each participant in the study experiences all of the conditions in the study.

Within-subjects

200

______ is a control used in within-subjects experiments where equal numbers of participants are randomly assigned to different orders of the conditions.

Counterbalancing

300

Because participants are being compared with themselves (under different conditions in a within subjects design), there are no between-group ______that contribute to the variability in the data

differences

400

One advantage of the within-subjects design is the reduction of ______ in the data.

error

500

Homogeneity of ______ is one the three test assumptions for the two-way between-subjects ANOVA. 

variances

Correlation/Regression

100

We cannot determine this from correlation and regression tests.

Causation

200

This type of analysis will help you predict a score on one variable from the score on another. 

Regression analysis

300

The larger the numerical value of ______, the stronger the relationship.

Pearson r

400

For linear regression, we can use this as the fit statistic.

r²

500

Unlike the distribution of sample means, the distribution of ______ values will stop at values of +1.0 on the high end and –1.0 on the low end.

r

Chi Square

100

______ is a common test used for relationships between categorical variables measured on nominal and ordinal scales.

Chi Square

200

For categorical variables, we need ______ tests.

nonparametric

300

A ______ error is more likely with a nonparametric tests than with parametric tests.

Type II

400

The chi-square test will examine the relationship between ______ variables in terms of what frequencies are expected if there is no relationship between the variables.

categorical

500

The number of participants expected in a cell category when there is no relationship between the variables is the ______ frequency.

expected