Discovering the Fundamentals of Statistics, Second Edition

Statistics becomes more useful when the numbers are connected to the questions behind them. Daniel T. Larose’s Discovering the Fundamentals of Statistics, Second Edition builds that connection step by step: first gathering and describing data, then using probability and inference to reason about what the data can—and cannot—show.

From raw data to a clear picture

The opening chapters introduce statistical thinking, data collection, and ways to describe information with graphs, tables, and numerical measures. Topics include sampling and selection bias, measures of center and variability, percentiles, outliers, and boxplots. Together, they give students a framework for summarizing data without losing sight of how it was gathered.

Explore patterns, probability, and variation

From scatterplots, correlation, and regression, the book moves into probability and probability distributions. Discrete and continuous variables, the binomial distribution, and the normal distribution lead into sampling distributions and the central limit theorem. This progression helps place individual observations in the broader context of chance and sample-to-sample variation.

Make and evaluate statistical claims

Later chapters address confidence intervals, hypothesis tests, and two-sample inference. Readers encounter procedures for means, proportions, and variability, along with ideas such as Type I and Type II errors and the power of a test. These methods provide a structured way to estimate population values and assess evidence.

Examples that bring the methods into focus

Case studies range across subjects including cell-phone use, health effects, and the Golden Ratio. Each chapter also includes vocabulary, formulas, review exercises, and a quiz, giving learners opportunities to revisit both concepts and techniques.

Designed for students studying introductory statistics, this textbook offers a sustained path from describing data to interpreting results and making evidence-based comparisons.