Analysis of variance
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Performing ANOVA in SPSS and Checking Assumptions: A Comprehensive Guide, Slides of Economic statistics
A step-by-step guide on how to perform a simple analysis of variance (anova) in spss and check the assumptions. The example uses the prices of a commodity in different cities as a case study. The assumptions of anova, the process of performing anova in spss, and checking the assumptions using spss.
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2011/2012
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Analysis of variance
Learn How to Perform a Simple ANOVA in SPSS and How to Check the Assumptions
Assumptions.
- Each group is an independent random sample from a normal population.
- Analysis of variance is robust to departures from normality
- The groups should come from populations with equal variances.
Analysis of Variance
Analysis of variance, or ANOVA, is a method of testing the null hypothesis that several group means are equal in the population, by comparing the sample variance estimated from the group means to that estimated within the groups.
A descriptive exploration
N = 8 7 6 5
City
A B C D
Price of commodity 1
50
40
30
Learn How to Perform a Simple ANOVA in SPSS and How to Check the Assumptions
Data are stored in the file “prices by city - anova example 1.sav”
Use the menu Analyze/General Linear, Model/Univariate
In the Univariate dialog box
Select the Price1 for the Dependent Variable
Select the City as the Fixed Factor(s)
- Click on the Save button
Under Predicted Values check Unstandardized
Under Residuals check Standardized
Click Continue
Click OK
Learn How to Perform a Simple ANOVA in SPSS and How to Check the Assumptions
Between-Subjects Factors
A 8
B 7
C 6
D 5
City
Value Label N
Tests of Between-Subjects Effects Dependent Variable: Price of commodity 1
315.574 a^3 105.191 55.746. 41585.412 1 41585.412 22038.273. 315.574 3 105.191 55.746. 41.513 22 1. 42814.267 26 357.088 25
Source Corrected Model Intercept CITY Error Total Corrected Total
Type III Sum of Squares df Mean Square F Sig.
a.R Squared = .884 (Adjusted R Squared = .868)
Checking assumptions
Predicted Value for PRICE
36 38 40 42 44 46 48 Standardized Residual for PRICE
.
-. -1. -1. -2.
GRAPH
/SCATTERPLOT(BIVAR)=pre_1 WITH zre_ /MISSING=LISTWISE.