Why Stata?

If you know Stata already, you don't have to read this post :)


FAQ:


Q - What is Stata?
A - Stata is a data analysis and Statistical Software by StataCorp, used frequently by researchers in the field of economics, political science, sociology, and others. Stata can help you with your data management, statistical analysis, visualization, regression analysis, etc. The word "Stata" is derived from two words "statistics" and "data," which more or less sums up what Stata does, i.e. statistics and data.





Q - Why use Stata?
A - Stata is a powerful data analysis and statistical software. But similar to Stata, there are a number of alternatives, just to name a few: SAS, R, SPSS and Minitab. Each of these packages despite doing the same job, have their own unique styles and their own strengths and weakness. Deciding to choose one of these pack is not easy, and very few has the resources to try all the packages out. I, having limited experience working with packages other than Stata, am going to report the review of expert users in the following. As you will see, Stata represents a good choice between these packages.

First, UCLA's Institute of Digital Research and Education compares SAS, Stata and SPSS, the summary of which is given below (click here for original article):

SAS is a package geared towards power users.  It has a steep learning curve and can be frustrating at first.  However, power users enjoy the its powerful data management and ability to work with numerous data files at once.

Stata offers a good combination of ease of use and power.  While Stata is easy to learn, it also has very powerful tools for data management, many cutting edge statistical procedures, the ability to easily download programs developed by other users and the ability to create your own Stata programs that seamlessly become part of Stata.

SPSS focuses on ease of use (their motto is "real stats, real easy"), and it succeeds in this area.  But if you intend to use SPSS as a power user, you may outgrow it over time. SPSS is strong in the area of graphics, but weak in more cutting edge statistical procedures lacking in robust methods and survey methods.


Second, Tobias Pfaff of University of Münster's Institute for Economic Education compares Stata, R, SAS and SPSS in his A Brief Introduction to Stata with 50+ Basic CommandsThe following table summarizes his verdict:


Third, ProStatServices (link here) compared Stata, SAS, R, SPSS and Minitab in an extensive 14 criteria. I have summarized the ranks in a table, which should help you make an informed decision on choosing one of the five statistical software.
A review of top five statistical software systems
Criteria Stata SAS R SPSS Minitab
1. Ease of use 2nd 3rd 3rd 1st 1st
2. Learning curve 2nd 3rd 3rd 1st 1st
3. Depth of menued procedures 3rd 3rd 3rd 1st 2nd
4. Range of statistical procedures offered 3rd 2nd 1st 4th 5th
5. Modifiability of analytical output specifications 2nd 1st 1st 2nd 3rd
6. Ease of transforming table output to formatting conventions (e.g., APA) 2nd 2nd 2nd 1st 2nd
7. Range, quality, and ease of use of graphical output offered 3rd 2nd 1st 2nd 4th
8. Speed of handling large data sets 3rd 1st 2nd 3rd 3rd
9. Ease and flexibility of data importation 3rd 2nd 1st 3rd 4th
10. Ease of results exportation 2nd 2nd 3rd 1st 3rd
11. Thoroughness and interpretability of results output = ====
12. Ease and flexibility of data set manipulation 1st3rd3rd1st2nd
13. Pricing for individuals 3rd4th1st5th2nd
14. Thoroughness and informativeness of documentation 1st2nd4th3rd3rd


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