Which of the following distributions is used to compare two variances?

• T – Distribution

• F – Distribution

• Normal Distribution

• Poisson Distribution

F-Distribution cannot take negative values.

• True

• False

Analysis of variance is a statistical method of comparing the ________ of several populations.

• standard deviations

• Variances

• Means

• proportions

The ______ sum of squares measures the variability of the observed values around their respective treatment means.

• Treatment

• Error

• Interaction

• total

To determine whether the test statistic of ANOVA is statistically significant, it can be compared to a critical value. What two pieces of information are needed to determine the critical value?

• sample size, number of groups

• mean, sample standard deviation

• expected frequency, obtained frequency

• MSTR (Mean Square Treatment), MSE

As variability due to chance decreases, the value of F will

• Increase

• stay the same

• Decrease

• can’t tell from the given information

When conducting a one-way ANOVA, the _______ the between-treatment variability is when compared to the within-treatment variability, the _______ the value of FDATA will tend to be.

• smaller, larger

• smaller, smaller

• larger, larger

• smaller, more random

Two-way and more complex ANOVAs are used only when:

• there is exactly one independent variable in the study design

• there are at least three independent variables in the design.

• We have two independent variables and two dependent variables in the study design.

• there is more than one independent variable in the study design.

In two-way ANOVA, a significant interaction tells us that

• at least one independent variable is statistically significant.

• at least two main effects are present in the study design.

• the pattern observed for one independent variable differs by the second independent variable.

• the effects of each variable in the study design are parallel.

Two-way and more complex ANOVAs are used when we have multiple dependent variables in our design.

• True

• False