(General ANOVA) and Independent Measures ANOVA
Repeated Measures ANOVA
Two-factor ANOVA
Correlation
Chi-square
100

In an ANOVA, the independent variable is called a

Factor

100
A repeated measures ANOVA is used when participants are ______ across treatment conditions

the same

100

Two-factor ANOVAs are a type of ______ design

factorial design
100

A correlation has a numerical value between ___ and ___

Between -1 and 1

100

Chi-square tests are non_________ tests

Non-parametric

200

Individual conditions that make up a factor are called

Levels

200

A key difference with calculating repeated measures ANOVA is that we remove _________ from the F-ratio

individual differences

200

Mean differences among the levels of one factor are referred to as the ______ of that factor

main effect

200

A correlation describes these three characteristics of the relationship between X and Y

The direction, form, and strength of the relationship

200

Chi-square tests are used when the variables are categorical and the data is presented as ___________

Frequency counts (or proportions is OK)

300

An ANOVA allows a researcher to compare how many groups or treatment conditions?

Three or more
300
One advantage of a repeated measures ANOVA is...

Desirable if the number of participants is small; eliminates most problems associated with individual differences

300
An example of a null hypothesis (H0) for a main effect of factor A is...

There is no difference between levels of factor A

300

A correlation of r = 0.0 indicates this

There is no consistency or relationship at all

300

In a chi-square test for goodness of fit, the observed frequency data is the number of individuals in a particular category from...?

The sample

400

An advantage of ANOVA is that by performing several comparisons in one hypothesis, it can reduce ________

Type I error (or testwise alpha level)

400

In a repeated measures ANOVA, the denominator of the F-ratio is called the...

Residual variance or error variance
400

When results of a two-factor ANOVA are shown in a graph, nonparallel lines suggest...

An interaction between the two factors

400

The direction and strength of a correlation of r = 0.45

A positive, moderate correlation

400

An example of a null hypothesis (H0) for a chi-square test for goodness of fit

There is no difference between proportions of each category

500

The F-ratio formula is ______ divided by _______

MSbetween divided by MSwithin

500

The F-ratio formula is _____ divided by ______

MSbetween divided by MSerror

500

Provide an example of a conclusion statement for an interaction

The effect of Factor A depends on the level of Factor B

500

The sum of products (SP) in the correlation formula represents this

How much variables X and Y vary together (covariability)

500

State the null hypothesis (H0) for a chi-square test of independence using two categorical variables

Category A is not related to category B

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