E-Books →Statistics with Python. 100 solved exercises for Data Analysis

This manual is designed for those who want to strengthen their skills in applied statistics with Python. The book is entirely made up of solved exercises, with detailed solutions and step-by-step explanations. The approach is practical and focused on business use cases, helping you understand how to apply theoretical concepts to real-world problems.
What you'll find inside:
Descriptive statistics: measures of central tendency, dispersion, and frequency distributions.
Hypothesis testing: testing statistical hypotheses with Python, p-values, and significance levels.
Probability and random variables: probability calculations and the most commonly used distributions.
Regression and correlation: linear regression models and analysis of variable dependence.
Probability distributions: practical use of distributions such as Normal, Binomial, and Poisson.
Who this book is for:
Aspiring data analysts and data scientists who want to apply statistics using Python.
Students and professionals looking to solidify their skills through practical exercises.
Anyone seeking a concrete and hands-on guide, with minimal theory, to tackle real problems.
If you want to develop a solid grasp of statistics and apply it practically with Python, this book will help you reach your goal.
The Author
Gianluca Malato was born in 1986 and is an Italian data scientist, lecturer, entrepreneur, and author. In 2010, he earned a Master's Degree with honors in Theoretical Physics of Disordered Systems from the University of Rome "La Sapienza" (thesis advisors: Giorgio Parisi and Tommaso Rizzo). He has worked for years as a data architect, project manager, data analyst, and data scientist for a major Italian company.
He has published several books and articles on Data Science on his blog yourdatateacher.com and on the online publication Towards Data Science (towardsdatascience.com). He received the "Top Writer" mention on Medium.com in the "Artificial Intelligence" category for his articles.