## How do you interpret an F value in ANCOVA?

F is between-groups variance divided by within-groups variance. If the computed p-value is small, then significant relationships exist. Adjusted means are usually part of ANCOVA output and are examined if the F-test demonstrates significant relationships exist.

## How do you write an ANCOVA result?

When writing up the results, it is common to report certain figures from the ANCOVA table. Click on the Options button and move the independent variable (diet) over to the Display Means For box, click on Compare main effects and select Bonferroni from the Confidence interval adjustment menu to request post hoc tests.

**How do you interpret ANCOVA intercept?**

The intercept represents the expected value (or mean) of Y when X1 and X2 are both equal to zero. If X1 is binary with values 0 and 1, then the intercept is the average of Y for the 0 group when X2 also equals zero.

### What does an ANCOVA test tell you?

ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of a categorical independent variable (IV) often called a treatment, while statistically controlling for the effects of other continuous variables that are not of primary interest, known as covariates (CV) or nuisance variables.

### What is repeated measure ANCOVA?

The repeated measures ANCOVA compares means across one or more variables that are based on repeated observations while controlling for a confounding variable. A repeated measures ANOVA model can also include zero or more independent variables and up to ten covariate factors.

**What is the null hypothesis for ANCOVA?**

Hypotheses: Null: There is no relationship between sex and SEI, controlling for the number of hours worked per week. Mean SEI for women = mean SEI for men. Research: There is a relationship between sex and SEI, controlling for the number of hours worked per week.

#### When should ANCOVA be used?

ANCOVA is used in experimental studies when researchers want to remove the effects of some antecedent variable. For example: Pre-test scores are used as covariates in pre-test & post-test experimental designs. 5.