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Rice Virtual Lab in Statistics

Descriptions and Examples for Various Statistical Computing Packages (UCLA)

provides resources to help you learn and use:

  • SAS
  • SPSS
  • Stata
  • Other programs: GPower, HLM, Mplus, R, Stat/Transfer, SUDAAN, WesVar

Data analysis examples -- "illustrating the application of different statistical analysis techniques using different statistical packages. Each page provides a handful of examples of when the analysis might be used along with sample data, an example analysis, explanation of the output, a short sample write-up, followed by references for more information. These pages merely introduce the essence of the technique and do not to provide a comprehensive description of how to use it."

Annotated output -- "These pages contain example programs and output with footnotes explaining the meaning of the output. This is to help you more effectively read the output that you obtain and be able to give accurate interpretations."

Which statistical test? -- "shows general guidelines for choosing a statistical analysis....covers a number of common analyses and helps you choose among them based on the number of dependent variables (sometimes referred to as outcome variables), the nature of your independent variables (sometimes referred to as predictors). You also want to consider the nature of your dependent variable, namely whether it is an interval variable, ordinal or categorical variable, and whether it is normally distributed (see What is the difference between categorical, ordinal and interval variables? for more information on this). The table then shows one or more statistical tests commonly used given these types of variables (but not necessarily the only type of test that could be used) and links showing how to do such tests using SAS, Stata and SPSS."