"Knowledge Base / Samples and SAS Notes," from the SAS Institute "Introduction to SAS Version 8.2," from the University of Virginia's ITC Division (via the Internet Archive) "Frequently-Asked Questions about SAS," from the Department of Statistics and Data Sciences at the University of Texas-Austin (via the Internet Archive) "Documentation for SAS Products and Solutions," from the SAS Institute "Articles on Statistical Computing - SAS Basics and SAS Topics" from the Social Science Computing Cooperative, at the University of Wisconsin-Madison " Tidy Data" - Written for R users, but applicable more generally.The Teaching Integrity in Empirical Research Project's recommended specifications and processes for working with data." Stata for Researchers: Project Management" - Written for Stata users, but applicable more generally.
#SAS VS SPSS HOW TO#
" Data Organization in Spreadsheets" - Excellent guidance and suggestions for how to format spreadsheets for data analysis.Some journals such as the American Economic Review and the American Journal of Political Science even require submission of syntax for cleaning and analyzing data as part of their submission policies on data availability.įor additional guidance on working with data, see the following: Simply put, syntax is documentation that spells out what you did to process and analyze the data and produce your findings, and access to that syntax thus shows others how you got your results. While there are learning curves of varying degrees of steepness with each of these applications, a syntax-based approach to working with data is a more robust and reproducible means of doing empirical analysis and is the flip side of proper citation with regard to the coin of transparency in quantitative research. These guides generally focus on using syntax to work with and analyze data in statistical software. The guides are very "from-the-ground-up" and cover multiple topics, from the basics of getting data into the program to various common data-management tasks to introductory data analysis. This page is a collection of links for help with using R, SAS, SPSS, and Stata.