Introduction to Stata

This tutorial is function-oriented, focusing on the data-management tasks most needed by data analysts working with sample survey data. It works up from basic tasks, such as how to drop variables, to the tasks needed for complex file organization, such as how to reshape and merge data files.

There is also a section on Analyzing Data from Sample Surveys. It explains which sampling weight command to use and whether to use svy or robust cluster to adjust for survey design effects.

These web pages assume that you are using Stata Version 13 or above for Windows.

If you would like to run the example commands, you need to copy the example Stata data files to your local PC. Click download sample data for instructions. If you're using a computer at the Carolina Population Center, the data are available to you on Q:\temp\statatut\.


See Stata Windows environment below for an orientation to the Windows interface. It also gives you sources of help beyond this tutorial.

Other resources available to help you learn Stata include the UCLA's IDRE Stat website, several introductory guides in the CPC library and others available from Stata Press, and Stata Corporation's Resources for learning Stata.

SAS Users: the SAS User's Guide to Stata may help you make the transition from SAS to Stata.

A simple example

  • input: putting data into Stata
  • generate: creating a new variable
  • list (or browse): viewing the contents of memory
  • save: saving memory in a permanent Stata-format file
  • log: capturing the results of Stata commands for printing
  • Stata's default actions
  • how data are stored in RAM

Using permanent Stata data files

  • clear: clearing Stata's memory
  • set memory: allowing enough space for the data
  • use: copying the file into memory
  • save,replace: saving changes

Describing the data

  • describe: names of variables
  • summarize: the mean, min, and max of variables
  • codebook: more univariate statistics
  • tabulate: frequencies and cross-tabulations
  • data types and data storage

Groups and subsets of data

  • if: do command for a subset of observations
  • sort: order observations by the values of a variable
  • by: do command for groups of observations (requires sort)
  • in: do command for a range of observations
  • relational, logical, and arithmetic operators
  • missing values

Changing the data

  • replace: change the values of a variable
  • recode: change the values of a variable
  • rename: change a variable name
  • label: labeling variables, values, and data files
  • drop: drop one or more variables
  • drop if: drop observations conditional on one or more variables
  • edit: editing the data file directly

Data cleaning

  • do: storing and executing commands in do-files
  • #delimit: writing long commands in do-files
  • /* */: documenting your do-files
  • finding and fixing outliers
  • duplicates: finding duplicate ids

Adding summary statistics to a data file

  • egen: add summary statistics to each observation
  • collapse: create file of summary statistics by groups

Combining data files

Reshaping a data file

  • reshape long: change variables to observations
  • reshape wide: change observations to variables

Documenting Your Work


  • histogram with normal curve fitted to it
  • graph box plot displayed for two groups
  • scatter plot
  • twoway scatter plot with regression line
  • other resources for learning graphics in Stata

Analyzing Data from Sample Surveys

Labor-Saving Techniques

Miscellaneous Tips and Tricks

Authors: Phil Bardsley, Kim Chantala, and Dan Blanchette

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