Libraries for Statistics and Probability

SciPy is a Python library that provides a wide range of functions for scientific and technical computing, including statistical functions, optimization algorithms, and linear algebra routines.

NumPy is primarily used for numerical operations and data manipulation. It provides efficient data structures and functions for working with large multi-dimensional arrays and matrices.

The stats package in R provides a comprehensive collection of functions for statistical analysis, including descriptive statistics, hypothesis testing, regression analysis, and time series analysis.

Pandas is primarily used for data manipulation and analysis. It provides data structures and operations for manipulating tabular data, including merging, filtering, grouping, and reshaping.

Statsmodels is a Python library that provides a collection of statistical models and tools for statistical analysis, including regression analysis, time series analysis, and generalized linear models.

SciPy provides a wide range of functions for probability distributions, random number generation, and statistical inference.

PyMC3 is a Python library that provides tools for Bayesian statistical modeling and inference, which is commonly used in machine learning applications.

Stan is an R package that provides a probabilistic programming language for Bayesian statistical modeling and inference.

Statsmodels provides a collection of statistical models and tools for time series analysis, including ARIMA models, exponential smoothing, and spectral analysis.