ANOVA concepts

The following are assumptions for ANOVA except:

• Variance must be homogenous

• There should be 4 or more independent groups

• Data must be normally distributed

• Randomly selected

ANOVA testing is used for ...

• Test for one mean

• Test for two means

• Test for three or more means

• Test for independence between two variables

Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:

A researcher want to determine whether there is an interaction between physical activity level and gender on blood cholesterol concentration in children.

• one-way ANOVA test

• two-way ANOVA test

Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:

A group of psychiatric patients are trying three different therapies: counseling, medication and biofeedback. They want to see if one therapy is better than the others.

• one-way ANOVA test

• two-way ANOVA test

ANOVA stands for ...

• Analysis of Variation

• Analysis of Variance

• Analysis of Variability

• A Non-Visual Analysis

Determine whether the following scenario should use a one-way ANOVA test or two-way ANOVA test:

A nutritionist is studying the effects of diet on cholesterol in men and women. She has data which reports cholesterol levels for men and women for three different diets (low-fat low calorie, Adkins diet, Mediterranean diet).

• one-way ANOVA test

• two-way ANOVA test

Which is NOT Assumptions and Design Consideration for One-Way ANOVA

• Normal distributed population

• Independence of error

• Homogeneity of viscoscity

• Data scale

Given the alternative hypothesis Ha: µ1 ≠ µ2 ≠ µ3 ≠ …….. µk. Which are the correct interpretations?

• The population mean is not same in all the groups

• At least one group is different from another

• Population means and hypothesized valueare equal

• The population mean is same in all the groups

This test is used when comparing groups on two different categorical variables which focuses on the interpreting main effects and interaction effects.

• One-way ANOVA

• Two-way ANOVA

• One-way t-Test

• Two-way t-Test

In two-way ANOVA, this effect is where the factorial analysis looks for significant changes in the dependent variable as a result of two or more of the independent variables working together

• Main Effect

• Sub Effect

• Interaction Effect

• Outcome Effect