Textbook in PDF format

This text is designed for two types of statistics courses. The early chapters, combined with a selection of the case studies, are designed for use in the second half of a two-semester (two-quarter) introductory statistics sequence for undergraduates with statistics or nonstatistics majors. Or, the text can be used for a course in applied regression analysis for masters or PhD students in other fields.
At first glance, these two uses for the text may seem inconsistent. How could a text be appropriate for both undergraduate and graduate students? The answer lies in the content. In contrast to a course in statistical theory, the level of mathematical knowledge required for an applied regression analysis course is minimal. Consequently, the difficulty encountered in learning the mechanics is much the same for both undergraduate and graduate students.
The challenge is in the application:
diagnosing practical problems, deciding on the appropriate linear model for a given
situation, and knowing which inferential technique will answer the researcher’s
practical question.
This takes experience, and it explains why a student with a nonstatistics major can take an undergraduate course in applied regression analysis and still benefit from covering the same ground in a graduate course