SAS vs Stata

The enterprise behemoth of stats meets the academic's statistical swiss army knife. Here's our take.

SAS

Nice Pick

The enterprise behemoth of stats. Powerful, expensive, and about as agile as a glacier.

Pros

• Rock-solid for handling massive datasets with complex statistical models
• Extensive library of pre-built procedures for advanced analytics
• Strong support and documentation for enterprise environments

Cons

• Proprietary licensing costs an arm and a leg
• SAS language feels archaic compared to modern open-source alternatives like R or Python

Stata

The academic's statistical Swiss Army knife. Powerful, but with a syntax that feels like it's from the '90s.

Pros

• Excellent for econometrics and panel data analysis
• Strong data management capabilities with built-in commands
• Widely used in academia, ensuring good community support

Cons

• Proprietary and expensive, especially for commercial use
• Syntax can be clunky and less intuitive compared to modern alternatives

The Verdict

Use SAS if: You want rock-solid for handling massive datasets with complex statistical models and can live with proprietary licensing costs an arm and a leg.

Use Stata if: You prioritize excellent for econometrics and panel data analysis over what SAS offers.

The Bottom Line

SAS wins

The enterprise behemoth of stats. Powerful, expensive, and about as agile as a glacier.