# How to Find Significance in ANOVA SPSS

Written by linda foley
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Social science researchers in psychology, sociology and political science fields use Statistical Package for the Social Sciences, or SPSS, to analyse data. They use ANOVA--which stands for analysis of variance--to analyse data in which there is one or more independent variables and a dependent variable. The term "significance" indicates whether the results of the SPSS analysis are due to the independent variables or chance. A significance of less than 0.05, which is less than 5 possibilities in 100 the result is due to chance, is acceptable in research.

Skill level:
Easy

## Instructions

1. 1

Review the output for your one-way ANOVA analysis in SPSS. Find the box on the bottom left of the output table that displays your dependent variable. The two categories will be "Between groups" and "Within groups." There will also be the total. Between Groups is the category of interest to you, it compares your groups. (See Reference 2 and 3)

2. 2

Look at the numbers in the row for the Between Groups category. The number in the next column to the right is the sum of squares (the sum of the squared deviations from the mean). (See Reference 2 and 3)

3. 3

Continue progressing to the right reviewing the numbers in the same row. The next number will be the degrees of freedom (df) which is calculated by subtracting 1 from the number of sample means. If you have four sample means, the df is 3. (See Reference 4)

4. 4

Continue viewing the figures across the same row until you come to the most important figures, the F value (the test statistic indicating the difference between groups) and Sig. The higher the F value, and the lower the Sig. the more significant the results. (See Reference 1)

5. 5

Find the most important data in the same row in the box to the far right -- Sig. (See Reference 2 and 3) Significance is the indication the difference between the groups is due to the independent variable not chance. (See Reference 1) Generally p < .05 (probability is less than .05) is considered significant. In other words, the possibility the difference between groups was due to chance is less than 5 out of 100. Sometimes you get Sig. of .000. The more zeros the higher the level of significance. (See Reference 1 and 2)

1. 1

Review the output for your factorial ANOVA analysis in SPSS. (See Reference 2 and 3) Find the box on the bottom left of the output table where you will see Main Effects, displaying your independent variables, for example age and education. Then you will see the 2-way interactions, for example age by education. (See Reference 2 and 3)

2. 2

Find the number to the far right on the row with your first independent variable (for example, age). A Sig of 0.05 or lower indicates there is a main effect for that variable. (See Reference 2 and 3)

3. 3

Follow the row of numbers to the far right on the line with your second independent variable (for example, education). A Sig. of .05 or lower indicates there is a main effect for that variable. (See Reference 2 and 3)

4. 4

Go to the row with the 2-way interactions (for example, age by education) and read the number to the far right under Sig. If the Sig is .05 or lower there is an interaction effect for those variables. (See Reference 2 and 3)

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