- One of the major advantages…of the analysis of variance…is that it allows you to use more than one…categorical predictor variable at a time.…Now the one-way analysis of variance…we had a single categorical variable…but you can combine them,…you can have more than one…and call it for instance…a two factor analysis of variance.…And things can get much more complicated than that.…You can have three or four or five factors,…you can have repeated factors thrown in there.…You can have what are called covariance.…We're not gonna deal with that.…We're gonna deal with a very simple version here.…
We're gonna look at the effect of two categorical variables…on a single scaled outcome.…Let's do that by going up to Analyze.…And as much as I'd like to say…that it would be under Compare Means…because that's where the one-way analysis of variance is,…the two factor analysis of variance is somewhere else.…It's under General Linear Model.…Sometimes called GLM,…not of course to be confused with…Generalized Linear Models…because you see that's a different set of things…
- Build charts, scatterplots, and box plots
- Calculate descriptive statistics such as means and standard deviations
- Use inferential statistics such as t-tests and chi-squares
- Enter and read data
- Create new variables and crosstabulations
- Model associations with correlations, contingency tables, and multiple-regression analysis
- Format and export presentations to share your data
Plus, learn how to extend the power of SPSS with Python and R. This course is ideal for first-time researchers and those who want to make the most of data in their professional and academic work.
Skill Level Beginner
1. Getting Started
2. Charts for One Variable
3. Modifying Data
4. Working with the Data File
5. Descriptive Statistics for One Variable
6. Inferential Statistics for One Variable
7. Charts for Associations
8. Statistics for Associations
9. Sharing Results
10. Extending SPSS
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