Perform (Analysis of Variance) in SPSS allows you to compare means across multiple groups to determine if there are statistically significant differences among them. Conducting ANOVA in SPSS can reveal significant differences in means among groups, providing deeper data insights and enabling informed research decision-making. Here’s a step-by-step guide to conducting ANOVA in SPSS:

Part I. Step-by-Step Guide for ANOVA in SPSS

Step 1: Open Your Data File

1. Launch SPSS on your computer.
2. Open your dataset by clicking on File > Open > Data and selecting the appropriate .sav file.

Step 2: Check Your Data

• Ensure that your data is properly formatted for ANOVA:
  • Dependent Variable: This should be a continuous variable (interval/ratio scale).
  • Independent Variable: This should be a categorical variable with two or more groups (nominal scale).

Step 3: Access the ANOVA Function

1. Go to the top menu and click on Analyze.
2. Hover over Compare Means.
3. Select One-Way ANOVA for comparing one continuous dependent variable across groups defined by one categorical independent variable.

Step 4: Select Your Variables

1. In the One-Way ANOVA dialog box:
   • Move your dependent variable into the Dependent List box.
   • Move your independent variable (factor) into the Factor box.

Step 5: Add Post Hoc Tests (if necessary)

• If your independent variable has more than two groups, you may want to perform post hoc tests to find out which specific groups differ:

1. Click on the Post Hoc… button.
2. Select a suitable post hoc test (e.g., Tukey, Bonferroni) based on your data and click Continue.

Step 6: Set Options (if necessary)

• Click on the Options… button if you want to include additional statistics like descriptive statistics, means plots, or homogeneity tests.

1. Check the boxes for Descriptive and Homogeneity tests.
2. Click Continue.

Step 7: Run the ANOVA

• Click OK to run the ANOVA analysis.

Step 8: Review the Output

1. SPSS will generate an output window with several tables:
   • Descriptive Statistics: Provides means and standard deviations for each group.
   • ANOVA Table: Look for the F-statistic and its significance (p-value) to determine if there are statistically significant differences between group means.
   • Post Hoc Tests: If performed, these tables will indicate which groups differ significantly from each other.

Step 9: Interpret the Results

1. In the ANOVA table:
   • Check the Sig. value (p-value). A value less than 0.05 typically indicates significant differences among groups.
2. For post hoc tests, look for specific group comparisons that indicate where the differences lie.

Step 10: Report Your Findings

• Summarize the results by including the F-value, p-value, and any significant group comparisons from the post hoc tests. Include descriptive statistics for clarity.