Describing categorical items:

• For categorical items like race/ethnicity, gender, location, etc. use descriptive statistics to describe how many people chose each category.  Creating tables, bar graphs, and pie charts is helpful for these items.

  • Choosing a graph: http://www.optimizesmart.com/how-to-select-best-excel-charts-for-your-data-analysis-reporting/

  • Bar graph and pie chart: http://www.wikihow.com/Make-a-Bar-Graph-in-Excel

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• Descriptive statistics in excel: http://www.excel-easy.com/examples/descriptive-statistics.html  

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• Descriptive statistics in SPSS: http://academic.udayton.edu/gregelvers/psy216/spss/descript1.htm

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Item and Reliability analysis (continuous scale items):

• Video learning: http://youtu.be/hpl9qvOB3lc?hd=1

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• Written how-to: https://statistics.laerd.com/spss-tutorials/cronbachs-alpha-using-spss-statistics.php

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Exploratory Factor Analysis (exploring how continuous items group together)

• Video learning: http://youtu.be/7SaNSUXISq4?hd=1

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• Written how to: https://statistics.laerd.com/spss-tutorials/principal-components-analysis-pca-using-spss-statistics.ph

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• Output Explained: https://stats.idre.ucla.edu/spss/output/factor-analysis/

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Parallel analysis (if needed)

• Parallel analysis is used when factor extraction and loadings aren’t clear.  This is used to verify factors aren’t due to chance (i.e. it looks like 3 factors but the third one is small and just due to chance in that dataset, really there are 2 factors). 

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• Courtney’s video: http://youtu.be/xP2u2tY41OA?hd=1  

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• Other video option (he has three parts but tends to ramble so hang in there) https://www.youtube.com/watch?v=T908yGVgjPk

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• Syntax comes from: https://people.ok.ubc.ca/brioconn/nfactors/parallel.sps