Introduction to Stata

Course dates

Auckland: 19–23 February 2018


Joanna Dipnall


This course assumes that participants have:

  1. Reasonable understanding of statistics to be able to comprehend the material covered, e.g. regression analysis.
  2. Some familiarity with a PC environment, including keyboard skills and understanding of file structures.
  3. Some experience using Microsoft Word and Excel or their equivalents.
  4. Some experience using a text editor such as Notepad or UltraEdit.

The course does not assume prior experience with Stata.

Course outline

The aim of the course is to provide participants with understanding and experience to undertake a basic research project in the social, financial or health sciences using Stata as the statistical tool. Stata is a comprehensive integrated package for data management, analysis and graphics. Stata v14 has a comprehensive GUI but this course focuses on the syntax as this will allow researchers to get the most out of Stata.
The course will be presented in a way that introduces beginners to survey research and at the same time extends the capabilities of more experienced researchers. Sample data sets will be provided, but participants are encouraged to bring some of their own data for analysis in Excel or ASCII format. Teaching and practice will be closely integrated, and individual assistance will be provided as needed.

Preparing Stata data sets. Introduction to the Stata system. Data analysis and session management. Looking at Stata data sets. Sources of help. Basic commands. Modifying data, editing, recoding, checking and tidying. Stata do-files (syntax files). Generating new variables. Inputting data into Stata. Introduction to Stata graphics. Outputting results to Word, etc. Handling strings and dates.
Starting the analysis. Initial univariate analysis: frequency distributions, exploratory data analysis. Initial bivariate analysis: cross-tabulations, correlations, t-tests and analysis of variance. Developing scales and indices: summated scales, factor analysis, alpha coefficient. More graphics including scatterplots, boxplots.
Regression analysis. Introduction to regression analysis: ordinary least squares. Checking assumptions with regression diagnostics. More graphics including regression diagnostics. Basic introduction to logistic regression and Poisson regression. Analysis of survey data. Introduction to sampling for surveys. Weighting observations.

Course text

Course notes will be supplied. No specific references are suggested, although participants are encouraged to bring any Stata documentation they may have. For an overview of the Stata package, please visit

Related courses/Experience

This course provides the researcher with experience in using Stata for quantitative data analysis, preferably following Introduction to Statistics or similar. Students who have completed courses such as SPSS for Researchers or Introduction to R will find this course relevant if they now need to use Stata.


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