What Is an Interaction Plot? An interaction plot (also called a profile plot in SPSS) is a line graph that shows how the effect of one factor on your outcome changes across the levels of another factor — the clearest way to see whether two variables interact. If you have not run the analysis yet,
Why SPSS Output Needs Managing Before It Reaches Word Run any analysis in SPSS and the Output Viewer fills up fast: a title, a notes block, a case processing summary, the table you actually need, a footnote or two, and a warning you did not ask for. Copy that whole window into Word and your
A plain bar chart shows only group means — it hides how much scores varied and how much you can trust each mean. Error bars fix that at a glance. In this guide, you will learn how to make a bar chart with error bars in SPSS three ways: the Chart Builder, the Legacy Dialogs,
You have run your ANOVA in SPSS, the output is full of numbers, and now you have to turn it into a sentence your supervisor will accept. This guide shows you exactly how to report ANOVA results in APA style (7th edition): which numbers to take from the SPSS output, how to format them, and
One-Way ANOVA vs Kruskal-Wallis: Which Test Does Your Data Actually Need? You have one categorical grouping variable and one continuous outcome, and you want to know whether the groups differ. Two tests compete for the job: the one-way ANOVA and the Kruskal-Wallis H test. They answer the same research question, but they make very different
Two Measurements, One Question: Which Test Fits Your Data? You measured the same people twice — before and after a training course, at baseline and follow-up, under two conditions — and now you need to know whether the scores really changed. Two tests compete for this job in SPSS: the paired-samples t-test and the Wilcoxon
Two Correlations, One Decision You have two variables and one question: are they related? In SPSS, that question usually leads to one of two tests — Pearson’s correlation or Spearman’s rank correlation. They look similar, they sit next to each other in the same dialog box, and they both produce a number between −1 and
Your Shapiro-Wilk Test Came Back Significant. Now What? You ran the normality check and the Shapiro-Wilk test came back significant. Your histogram leans to one side and the Q-Q plot curves away from the line. If your next step is a t-test, an ANOVA, or a regression, that feels like a problem — because those
Why Checking Normality Matters Before You Run a Test Almost every parametric test in SPSS — the independent-samples t-test, one-way ANOVA, Pearson correlation, linear regression — comes with a small-print condition: your data should be approximately normally distributed. Skip that check and you risk reporting a p-value from a test whose assumptions your data never
The chi-square test is the default choice for testing whether two categorical variables are related. But it relies on an approximation that breaks down when your sample is small. When one or more cells in your table have very low expected counts, the p-value chi-square gives you can be misleading. That is exactly when Fisher’s