The unifying theme of this text is the use of models in statistical data analysis.
In your introductory statistics course, you saw many facets of statistics but you probably did little if any work with the formal concept of a statistical model. To us, modeling is a very important part of statistics. In this book, we develop statistical models, building on ideas you encountered in your introductory course. We start by reviewing some topics from Stat 101 but adding the lens of modeling as a way to view ideas. Then we expand our view as we develop more complicated models.You will find a thread running through the book:
Choose a type of model.
Fit the model to data.
Assess the fit and make any needed changes.
Use the fitted model to understand the data and the population from which they came.
We hope that the Choose, Fit, Assess, Use quartet helps you develop a systematic approach to analyzing data.
Modern statistical modeling involves quite a bit of computing. Fortunately, good software exists that enables flexible model fitting and easy comparisons of competing models. We hope that by the end of your Stat2 course, you will be comfortable using software to fit models that allow for deep understanding of complex problems.
