View our tutorials for analyzing data using inferential statistical methods in SPSS.

Part 1: Inferential Statistics for Association

In Part I, we cover common inferential statistics for testing the relationship or association between variables.

• Pearson CorrelationPearson correlation (Analyze > Correlate > Bivariate) is used to assess the strength of a linear relationship between two continuous numeric variables.
• Chi-square Test of IndependenceThe Chi-Square Test of Independence is used to test if two categorical variables are independent of each other.

Part 2: Inferential Statistics for Comparing Means

In Part 2, we cover common inferential statistics for testing and comparing means.

• One Sample t TestOne sample t tests (Analyze > Compare Means > One Sample T Test) are used to test if the mean of a continuous numeric variable is equal to a hypothesized value of the population mean.
• Paired-Samples T TestPaired t tests (Analyze > Compare Means > Paired-Samples T Test) are used to test if the means of two paired measurements, such as pretest/posttest scores, are significantly different.
• Independent Samples T TestIndependent samples t tests (Analyze > Compare Means > Independent-Samples T Test) are used to test if the means of two independent groups are significantly different.
• One-Way ANOVAOne-Way ANOVA (Analyze > Compare Means > One-Way ANOVA) is used to test if the means of two or more groups are significantly different.