SPSS is easy to open and easy to misuse. Most problems come from how the data was prepared, not from the software. Follow this checklist before you click a single test.
1. Prepare your data before importing
- Use one row for each respondent and one column for each variable.
- Give every variable a short name with no spaces, such as age or sex.
- Code answers with numbers (for example 1 = Male, 2 = Female) and keep a code list.
2. Set up Variable View
Open Variable View and complete the columns: Name, Type, Label, Values and Measure. Values lets you attach words to your codes, and Measure (Nominal, Ordinal or Scale) tells SPSS which tests make sense.
3. Clean the data first
- Run Frequencies on each categorical variable to spot impossible values such as a code 7 when your codes stop at 3.
- Check numbers with Descriptives (minimum, maximum and mean) to find typing errors such as an age of 250.
- Decide how to treat missing answers and be consistent.
4. Describe your sample
Start with simple descriptions: counts and percentages for categories, and the mean and standard deviation for numbers. Readers need to see who is in your study before they see your results.
5. Choose a test that fits your question
- Two categorical variables (for example sex and vaccination status): Chi-square test.
- Compare a number between two groups: independent-samples t-test.
- Compare a number between three or more groups: one-way ANOVA.
- Relationship between two numbers: correlation, or regression if you want to predict.
6. Report clearly
Report the test used, the result and the p-value, then explain in plain words what it means. Avoid saying a result is important only because it is significant: also look at the size of the difference.
Need help?
AfroTechna can analyse your data in SPSS, R, Python or Excel and train your team to do it themselves. You stay the author of your research.