One-Way ANCOVA - Example

The Study: Administrators at Parday University are concerned about their poor student achievement and are examining all possible causes. They ask you to conduct a study into the amount of sleep students get. You have been asked to find out if there is a difference in the average number of hours slept among students based on year in school (Freshmen, sophomore, junior, senior) while controlling for the effect of gender.

Decision Path: Inferential / Difference / Scaled Data / Normal Distributions / 1 Dependent Variable / 1

Independent Variable / 2 levels / Non-Repeated / Covariate = One-Way Analysis of Covariance (ANCOVA).

Other Paths to ANCOVA: Inferential / Difference / Scaled Data / Normal Distributions / 1 Dependent Variable / 1

Independent Variable / 3 levels / Non-Repeated / Covariate = One-Way Analysis of Covariance (ANCOVA).

Inferential / Difference / Scaled Data / Skewed Distributions / 1 Dependent Variable / 1 Independent Variable / 2 or 3 levels / Non-Repeated / Covariate = One-Way Analysis of Covariance (ANCOVA).

The Hypothesis: There is a statistically significant difference between the amounts of sleep freshmen get at the beginning compared to the end of the semester after controlling for the effect of gender.

The Null-hypothesis: There is no statistically significant difference between the amounts of sleep freshmen get at the beginning compared to the end of the semester after controlling for the effect of gender.

Question: Do we have enough evidence to reject the null hypothesis?

The Decision rule: If the probability that we are wrong is .05 or 5 out of 100 times we will reject the null-hypothesis in other words, accept the hypothesis.

This is the Dependent Variable

This is the Independent Variable

This is the Covariate

There is a statistically significant difference among

years in school after taking out the effect of gender in terms of

average hours slept.

Gender is not a significant Covariate

Result: A one-way between subjects ANCOVA was calculated to examine the effect of year in school on hours of sleep controlling for the effect of gender. Gender was not significantly related to hours of sleep F(1, 115) = .715, p = .400. Year in school did show significant difference in terms of hours of sleep F(3, 115) = 9.085, p = .000 after eliminating the effect of gender

Go to the next page to see where these numbers came from:

Result: A one-way between subjects ANCOVA was calculated to examine the effect of year in school on hours of sleep controlling for the effect of gender. Year in school did show significant difference in terms of hours of sleep F(3, 115) = 9.085, p = .000 after eliminating the effect of gender. Gender was not a significant covariate F(1, 115) = .715, p = .400.