Introduction to Statistics and Data Analysis

Statistics begins with questions about real data: how it was collected, what patterns it reveals, and how much confidence to place in an apparent result. Introduction to Statistics and Data Analysis builds those ideas into a full introductory course, moving from describing data to probability and statistical inference.

From data collection to sound conclusions

Roxy Peck and Chris Olsen begin with the role of statistics and the data-analysis process, then turn to sampling, observational studies, and experimental design. This early emphasis gives students a framework for thinking about where data come from before deciding what the data can support.

See the data before modeling it

Chapters on graphical and numerical methods introduce ways to summarize categorical, numerical, and bivariate data. Students encounter displays such as histograms and boxplots, alongside measures of center and variability. The treatment then develops correlation and regression, including methods for assessing a fitted line and considering nonlinear relationships.

Build the foundations for inference

The text proceeds through probability, random variables, and probability distributions before addressing sampling variability. Its later chapters cover point estimates, confidence intervals, hypothesis tests, comparisons of two populations or treatments, categorical-data analysis, linear regression inference, multiple regression, and analysis of variance. Nonparametric methods appear in an optional final chapter.

Practice interpreting, not just calculating

Activities, chapter reviews, technology notes, and selected answers to odd-numbered exercises support the chapter sequence. Repeated attention to interpreting and communicating statistical results helps connect calculations with the questions they are meant to answer. Optional topics include logistic regression and bootstrap confidence intervals.

A structured introduction to statistics

This seventh edition is suited to students taking an introductory college statistics course and to instructors looking for a text that spans data description, probability, and widely used inferential methods. Its broad progression offers a clear route from asking statistical questions to evaluating evidence and explaining conclusions.