© Gayathri Rajagopalan 2021
G. RajagopalanA Python Data Analyst’s Toolkithttps://doi.org/10.1007/978-1-4842-6399-0_9

9. Statistics and Probability with Python

Gayathri Rajagopalan1  
Bangalore, India

In the previous chapter, we learned about how to apply your knowledge of data analysis by solving some case studies.

Now, in the final part of this book, we learn about essential concepts in statistics and probability and understand how to solve statistical problems with Python. The topics that we cover include permutations and combinations, probability, rules of probability and Bayes theorem, probability distributions, measures of central tendency, dispersion, skewness and kurtosis, sampling, central limit theorem, and hypothesis testing. We also ...

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