Join Barton Poulson for an in-depth discussion in this video Comparing means with two categorical variables: ANOVA, part of SPSS Statistics Essential Training.
- 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…
Author
Barton Poulson
Released
11/17/2014- 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
Duration
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Introduction
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Welcome1m 13s
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1. Getting Started
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Touring the interface7m 48s
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Setting options5m 17s
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Getting help2m 52s
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Using the built-in data sets2m 22s
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2. Charts for One Variable
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3. Modifying Data
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Recoding variables6m 49s
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Reversing values with syntax6m 56s
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Creating dummy variables3m 19s
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Recoding with Visual Binning5m 32s
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Computing new variables6m 52s
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Automatic data preparation3m 46s
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4. Working with the Data File
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Selecting cases5m 8s
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Splitting files3m 57s
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5. Descriptive Statistics for One Variable
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6. Inferential Statistics for One Variable
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7. Charts for Associations
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Side-by-side boxplots3m 34s
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Scatterplots4m 33s
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Scatterplots by groups2m 59s
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3D scatterplots3m 16s
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Scatterplot matrices3m 32s
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Heat maps3m 23s
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Choropleth for one variable4m 54s
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Choropleth for two variables3m 28s
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8. Statistics for Associations
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Correlation5m 23s
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Bivariate regression6m 46s
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Multiple regression10m 20s
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Automatic Linear Modeling5m 45s
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9. Sharing Results
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Exporting charts and tables4m 24s
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Web reports2m 33s
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The Smartreader3m 23s
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10. Extending SPSS
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Using Python in SPSS4m 40s
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Using R in SPSS10m 2s
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Conclusion
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Next steps1m 23s
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Video: Comparing means with two categorical variables: ANOVA