ANOVA Lecture ACTIVITY 8

CHART FOR STATISTICAL ANALYSIS

ANOVA
One-way Analysis of Variance (ANOVA) is used with one categorical independent variable and one continuous variable. The independent variable can consist of any number of groups (levels).
A statistical technique by which we can test if three or more means are equal. It tests if the value of a single variable differs significantly among three or more levels of a factor.
Example:

Problem: Susan Sound predicts that students will learn most effectively with a constant background sound, as opposed to an unpredictable sound or no sound at all. She randomly divides twenty-four students into three groups of eight. All students study a passage of text for 30 minutes. Those in group 1 study with background sound at a constant volume in the background. Those in group 2 study with noise that changes volume periodically. Those in group 3 study with no sound at all. After studying, all students take a 10 point multiple choice test over the material. Their scores follow:
Group

Test Scores

1) Constant sound

7

4

6

8

6

6

2

9

2) Random sound

5

5

3

4

4

7

2

2

3) No Sound

2

4

7

1

2

1

5

5

Ho: X1 = X2 = X3
Procedure:
Variable view: follow format and labels

Data View:

One-way ANOVA

Dialog box of One-Way ANOVA
-

test scores should be placed in the dependent list and sound background in the Factor

Select Post Hoc then after, in the dialog box check Tuckey then click Continue and OK (One-way ANOVA).

The Output would be:

Interpretation
Susan can conclude that her hypothesis may be supported. The means are as she predicted, in that the constant music group has the highest score. However, the significant F only indicates that at least two means are significantly different from one another, but she can't know which specific mean pairs significantly differ until she conducts a post-hoc analysis (e.g., Tukey's HSD)

Two-Way ANOVA
A Two-Way ANOVA is useful when we desire to compare the effect of multiple levels of two