Annova
Two-way ANOVA using SPSS
Introduction
The two-way ANOVA compares the mean differences between groups that have been split on two independent variables (called factors). You need two independent, categorical variables and one continuous, dependent variable.
Assumptions
* Dependent variable is either interval or ratio (continuous) * The dependent variable is approximately normally distributed for each combination of levels of the two independent variables. * Homogeneity of variances of the groups formed by the different combinations of levels of the two independent variables. * Independence of cases (this is a study design issue and is not addressed by SPSS).
Example
A researcher was interested in whether an individual's interest in politics was influenced by their level of education and their gender. They recruited a random sample of participants to their study and asked them about their interest in politics, which they scored from 0 - 100 with higher scores meaning a greater interest. The researcher then divided the participants by gender (Male/Female) and then again by level of education (School/College/University).
Setup in SPSS
In SPSS we separated the individuals into their appropriate groups by using two columns representing the two independent variables and labelled them "Gender" and "Edu_Level". For "Gender", we coded males as "1" and females as "2", and for "Edu_Level", we coded school as "1", college as "2" and university as "3". The participants interest in politics was entered under the variable name, "Int_Politics". To know how to correctly enter your data into SPSS in order to run a two-way ANOVA, please read our Entering Data in SPSS tutorial, where there is a specific example. The data setup can be seen in the diagram below. We have given our data text labels.
Testing of Assumptions
To determine whether your dependent variable is normally distributed for each combination of the levels of the two independent variables see
Introduction
The two-way ANOVA compares the mean differences between groups that have been split on two independent variables (called factors). You need two independent, categorical variables and one continuous, dependent variable.
Assumptions
* Dependent variable is either interval or ratio (continuous) * The dependent variable is approximately normally distributed for each combination of levels of the two independent variables. * Homogeneity of variances of the groups formed by the different combinations of levels of the two independent variables. * Independence of cases (this is a study design issue and is not addressed by SPSS).
Example
A researcher was interested in whether an individual's interest in politics was influenced by their level of education and their gender. They recruited a random sample of participants to their study and asked them about their interest in politics, which they scored from 0 - 100 with higher scores meaning a greater interest. The researcher then divided the participants by gender (Male/Female) and then again by level of education (School/College/University).
Setup in SPSS
In SPSS we separated the individuals into their appropriate groups by using two columns representing the two independent variables and labelled them "Gender" and "Edu_Level". For "Gender", we coded males as "1" and females as "2", and for "Edu_Level", we coded school as "1", college as "2" and university as "3". The participants interest in politics was entered under the variable name, "Int_Politics". To know how to correctly enter your data into SPSS in order to run a two-way ANOVA, please read our Entering Data in SPSS tutorial, where there is a specific example. The data setup can be seen in the diagram below. We have given our data text labels.
Testing of Assumptions
To determine whether your dependent variable is normally distributed for each combination of the levels of the two independent variables see