PROBABILITY & STATISTICS FOR STEM: A Complete Course in Probability Theory, Statistical Inference, and Data Analysis by Mir Hossain

Master probability and statistics the way STEM students actually learn: clear concepts + visual intuition + lots of fully worked problems. Probability & Statistics for STEM is a complete, student-friendly course built to help you understand the “why”, practice the “how,” and gain the confidence to solve exam-style questions quickly and correctly. Each topic is explained in plain language, reinforced with examples, and followed by targeted practice so you can improve step by step. What you’ll learn Probability fundamentals: counting, conditional probability, Bayes’ rule, random variables Core distributions: binomial, geometric, Poisson, exponential, normal, and more Descriptive statistics and data visualization: summaries, plots, correlation, regression basics Sampling and the Central Limit Theorem (CLT) Statistical inference: confidence intervals, hypothesis tests, p-values, and interpretation Practical problem-solving strategies you can reuse across STEM courses What makes this book different Hundreds of worked examples with clear, step-by-step solutions Lots of practice problems for each concept (with answers and solutions) Visual explanations that make abstract ideas stick Chapter reviews and tests to build exam readiness Designed for engineering, computer science, biology, chemistry, physics, and data-focused majors Read more