Statistics Every Programmer Needs

"Statistics Every Programmer Needs" is a practical guide on applying statistical and quantitative methods to programming tasks using Python. The book thoroughly covers both basic techniques (descriptive statistics, hypothesis testing) and advanced techniques (linear regression, time series, Markov chains, optimization solutions). Each standalone section includes well-documented Python examples: from predicting splits in ultramarathons to classifying raisins by morphological features and analyzing system reliability. You will learn how to build predictive models and simulations, interpret and verify results with scientific rigor, and make informed decisions under uncertainty. Practical exercises and reproducible code snippets will help you master statistics "from theory to practice" and turn raw data into valuable insights.