What are the top statistical analysis software tools for conducting regression analysis?

R language works well with linear and logistic regression. It is constructed in a way to best visualize the results( it is the best programming language for viewing charts / tables of regression analytics) It has lot of packages which can be used to enhance the experience

R is an open free source and requires a good knowledge of programming offers a wide range of regression tools and packages including lm, and glm as generalized linear models

Python language is the easiest to read among the main stream programming languages. Lot of complex data structures can be handled well using pandas library. Any pre processing data analysis is best done with python specially if the data size is very huge.

SAS is used at institutions which require very high governance process. Given SAS is a paid software, there is structured support available and there are less frequent changes. Moreover chances of any vulnerabilities are less making it more robust language. Drawback of using SAS is that code is not so easy to understand for someone unfamiliar with the language. Small logic changes may need lot of code change

Excel hand in is very handy for quick sense check and trying out some combinations where you can actually play around with the numbers. The drawback of excel is that results of all statistical results is not easily available , plus you cannot build models on very large data set or with too many variables. It is something which is used by senior managers a lot to formulate some hypothesis before using sophisticated programming languages such as python and R for finalizing the model.

SPSS program offers a wide range of regression tools as linear, logistic, and ordinal regression, it is a user-friendly software and this makes it easy for inexperienced analysts to get to grips with the platform.

Stata is sometimes an overlooked software for statistical modeling. Historically, it has supported those engaged in Econometrics research and analysis. If you ever have to do an Ordinary Least Squares (OLS) regression, there are so many online tutorials that show you how easy it is to do in Stata. Much like SAS or SPSS, it aims for a balance of ease of use and robust statistical analysis.

Stata program offers robust regression analysis including a wide range of methods as basic and advanced regression methods like linear, logistic, Poisson, Quartile, probit, and much more, it is a user-friendly interface and you can also write commands.

C++ is used at places where speed is of the essence and the data is very huge. For example in high frequency trading models. The code is complex but the language is easy to learn for someone with programming background.