Stata is a statistical software package commonly used for data analysis, data management, and graphics.
Starting from $57/month for students
Best statsmodels Alternatives ranked by AI · updated Aug 2026
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statsmodels is an open-source Python library for statistical modeling and econometrics used by analysts, researchers, and developers. It includes linear and generalized linear models, discrete choice, time series, robust statistics, and statistical tests within Python workflows.
Top 6 statsmodels alternatives
gretl is an open-source software for econometric analysis. It provides a wide range of functionalities for data analysis, model estimation, and forecasting.
EViews is a commercial econometrics and forecasting package for economists, analysts, and academic researchers. It emphasizes time-series modeling, forecasting, data management, and...
Pros
- Stronger time-series and forecasting interface than SHAZAM
- More accessible graphical workflow for applied economists
- Includes purpose-built tools for econometric forecasting
Cons
- Commercial licensing is less flexible than free R or Gretl
- Narrower general-purpose programming ecosystem than Python or R
- Less strong for broad statistical computing outside econometrics
Paid; pricing varies by license
SAS is a software suite used for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics.
Custom pricing
LIMDEP is a desktop econometrics package for researchers, analysts, and students working with cross-sectional, panel, and limited dependent variable models. It supports...
Pros
- Strong coverage of limited dependent variable and discrete choice models
- Includes specialized econometric procedures that are less prominent in general statistics packages
- Designed for applied researchers who need model-oriented workflows
Cons
- Less widely used and documented than Stata or R
- Smaller user community and third-party ecosystem
- Less flexible for general-purpose programming and data engineering than R or Python
6
R is a programming language and software environment for statistical computing and graphics.
Pros
- Specialized for statistical analysis
- Vast number of packages for data manipulation and visualization
Cons
- Steep learning curve for beginners
- Not as versatile for general-purpose programming
Free
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