One way ANOVA

IBM SPSS Step-by-Step Guide: One-Way ANOVA

Note: This guide is an example of creating ANOVA output in SPSS with the grades.sav file. The variables shown in this guide do not correspond with the actual variables assigned in Unit Assignment 1. Carefully follow the instructions in the assignment for a list of assigned variables. Screen shots were created with SPSS 21.0.

Unit Assignment 1: One-Way ANOVA

Refer to the assignment instructions for a list of assigned variables. The example variables “year” and “final” are shown below.

Step 1. Open grades.sav in SPSS.

To complete Section 2 of the DAA, you will generate SPSS output for a histogram, descriptive statistics, and the Shapiro Wilk test, which are reviewed in previous Step-by-Step guides. The Levene test (homogeneity of variance) is reviewed in the steps below.

To conduct the one-way ANOVA in SPSS, select Analyze ( Compare Means ( One-Way ANOVA…

The One-Way ANOVA window appears. Move the assigned Unit assignment dependent variable into the Dependent List area. Move the assigned Unit assignment independent variable in the Factor area. The examples of “final” and “year” are shown below.

Next, select the “Options” button. Select “Homogeneity of variance test” (Levene test) for Section 2 of the DAA. Select “Descriptive” and “Means Plot” for Section 4 of the DAA. Press Continue.

Next, select the Post Hoc button and check the Tukey option for multiple comparisons. Press Continue and OK.

A string of ANOVA output will appear in SPSS. All output below is for the example variable “final” not assigned in Unit Assignment 1. Copy and paste the Levene test output into DAA Section 2 and interpret it for the homogeneity of variance assumption.

Test of Homogeneity of Variances
final
Levene Statistic	df1	df2	Sig.
.866	3	101	.462

Copy and paste the Means Plot into DAA Section 4 and interpret it.

The Descriptives output is pasted in DAA Section 4 along with the report of means and standard deviations of the dependent variable at each level of the independent variable.

Descriptives
final
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean	Minimum	Maximum
					Lower Bound	Upper Bound
Frosh	3	59.33	5.859	3.383	44.78	73.89	55	66
Soph	19	62.42	6.628	1.520	59.23	65.62	48	72
Junior	64	61.47	8.478	1.060	59.35	63.59	40	75
Senior	19	60.89	7.951	1.824	57.06	64.73	43	74
Total	105	61.48	7.943	.775	59.94	63.01	40	75

The ANOVA output is also pasted into DAA Section 4 and interpreted.

ANOVA
final
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	37.165	3	12.388	.192	.902
Within Groups	6525.025	101	64.604
Total	6562.190	104

Finally, if the overall ANOVA is significant, the post hoc output is pasted into DAA Section 4 and interpreted.

Multiple Comparisons
Dependent Variable: final
Tukey HSD
(I) Year in school	(J) Year in school	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
					Lower Bound	Upper Bound
Frosh	Soph	-3.088	4.993	.926	-16.13	9.96
	Junior	-2.135	4.748	.970	-14.54	10.27
	Senior	-1.561	4.993	.989	-14.61	11.48
Soph	Frosh	3.088	4.993	.926	-9.96	16.13
	Junior	.952	2.100	.969	-4.53	6.44
	Senior	1.526	2.608	.936	-5.29	8.34
Junior	Frosh	2.135	4.748	.970	-10.27	14.54
	Soph	-.952	2.100	.969	-6.44	4.53
	Senior	.574	2.100	.993	-4.91	6.06
Senior	Frosh	1.561	4.993	.989	-11.48	14.61
	Soph	-1.526	2.608	.936	-8.34	5.29
	Junior	-.574	2.100	.993	-6.06	4.91