#IBM SPSS STATISTICS 22 TUTORIAL HOW TO#

#IBM SPSS STATISTICS 22 TUTORIAL HOW TO#

In this 'quick start' guide, we show you how to carry out a two-way ANOVA using SPSS Statistics, as well as interpret and report the results from this test. Alternatively, if you have a continuous covariate, you need a two-way ANCOVA. Note: If you have three independent variables rather than two, you need a three-way ANOVA. For example, is the effect of gender (male/female) on test anxiety influenced by educational level (undergraduate/postgraduate)? Additionally, if a statistically significant interaction is found, you need to determine whether there are any 'simple main effects', and if there are, what these effects are (we discuss this later in our guide). The interaction term in a two-way ANOVA informs you whether the effect of one of your independent variables on the dependent variable is the same for all values of your other independent variable (and vice versa). Alternately, you may want to determine whether there is an interaction between physical activity level and gender on blood cholesterol concentration in children, where physical activity (low/moderate/high) and gender (male/female) are your independent variables, and cholesterol concentration is your dependent variable.

For example, you could use a two-way ANOVA to understand whether there is an interaction between gender and educational level on test anxiety amongst university students, where gender (males/females) and education level (undergraduate/postgraduate) are your independent variables, and test anxiety is your dependent variable. The primary purpose of a two-way ANOVA is to understand if there is an interaction between the two independent variables on the dependent variable. The two-way ANOVA compares the mean differences between groups that have been split on two independent variables (called factors). Two-way ANOVA in SPSS Statistics Introduction

Ibm spss statistics 22 tutorial