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Teaching your course with Stata provides your students with tools and skills that translate to their professional life. Stata is affordable, is easy to use and learn, and provides all the statistics, data manipulation, visualization, and reporting that your students need.
regress y x1 x2
logistic y x1 x2
Among all common statistical packages, Stata is the best for students with very different programming backgrounds: Stata is very easy to pick up for students with no programming experience at all; at the same time, for students with extensive programming experience, Stata provides sufficient flexibility for them to develop their own codes and ado-packages.
Ling Cen, Associate Professor of Finance, The Chinese University of Hong Kong
| Our web resources page provides many links to resources that make introducing your students to Stata easy, including Stata for Students, the Online Stata tutorial, and Stata learning modules. These resources provide easy-to-follow instructions and examples to help students get up and running with Stata. We also have these Stata cheat sheets and dates and times guide that you can share. | |
| Our YouTube channel is full of videos and short tutorials that can assist you and your class with using Stata. Browse all our video tutorial playlists by subject on the Stata website or by discipline on YouTube. | |
| Our NetCourses are convenient, web-based courses for Stata users of all experience levels, from beginning to advanced. | |
| Our Ready. Set. Go Stata. webinars are great way to introduce new users to Stata. | |
| Interested in which books and Stata features apply to your discipline? We've created a page just for you. | |
| Stata's documentation includes fully worked examples using downloadable datasets so you can work along or even extend the analyses. | |
| Browse articles written by Stata developers on the The Stata Blog, or see what's new on Statalist, the offical Stata forum moderated by users. |
6-month or 1-year license: If your students only need Stata for one course, they can purchase a 6-month or 1-year license at an even more affordable rate.
1-week license: Only need Stata for a few days? Instructors can request a short-term license for free.
Campus and department licenses: Many universities have campus-wide licenses or departmental licenses your students can easily access. To see if your school has one, email us.
Introductory and advanced statistics: Teach an introduction to statistics course, including summary statistics, tabulations, tests of means and proportions, linear regression, and ANOVA. Or teach advanced topics such as time series, panel/longitudinal data, survey data analysis, survival analysis, multilevel models, matrix programming, and much more. View a comprehensive list.
Visualization: Create hundreds or thousands of graphs in a reproducible manner, and export them to EPS or TIF for publication, to PNG or SVG for the web, or to PDF for viewing. With the integrated Graph Editor, you click to change anything about your graph or to add titles, notes, lines, arrows, and text.
Data manipulation: Combine and reshape datasets, manage variables, and collect statistics across groups or replicates. You can easily cut and paste data from spreadsheets or web tables into Stata. You can work with numeric and string data types, including strings up to 2 billion characters. Stata also has advanced tools for managing specialized data such as survival/duration data, time-series data, panel/longitudinal data, categorical data, multilevel data, multiple-imputation data, discrete choice data, and survey data.
Reporting: With Stata's reporting features, you can easily incorporate Stata results and graphs with formatted text and tables in Word, PDF, HTML, and Excel formats. Take advantage of Stata's integrated versioning to create reproducible reports. Dynamic documents can be updated as your data change.
All in one package: When you buy Stata, you get everything for your statistical, graphical, and data analysis needs. You do not need to buy separate modules or specialized software for advanced methods such as multiple imputation and structural equation modeling.