## Introductory Statistics for the Health Sciences: Table of Contents

**Chapter 1: The Frontier Between Knowledge and
Ignorance.**

This chapter describes the role of
statistics within the larger realm of research, with an emphasis
on kinds of research and variables. No other introductory
statistics textbook provides such a thorough explanation of the
context in which statistics are used.

**Chapter 2: Describing Distributions with
Statistics: Middle, Spread and Skewness.**

These characteristics of data sets are described by the
statistics in this chapter.

**Chapter 3: Exploring Data Visually. **

Statistics can be revealing -- or they can conceal important
details about a data set. In this chapter we cover a large
number of common and not-so-common graphs that can help
researchers to understand and communicate their results.

**Chapter 4: Relative Location and Normal
Distributions.**

We can describe a score's
location within a set of numbers, a fundamental skill that will
generalize to many topics in the book.

**Chapter 5: Bivariate Correlation. **

Now we take two variables at a time and look at a relationship
between them.

**Chapter 6: Probability and Risk. **

This chapter sounds a lot scarier than it is. Instructors
may choose to cover only part of this chapter, which contains
many topics, including conditional probability, sensitivity,
specificity, and relative risk.

**Chapter 7: Sampling Distributions and Estimation.**

This chapter begins a transition from descriptive statistics to
the kinds of statistics needed for testing hypotheses and using
samples to estimate what may be happening in the
population.

**Chapter 8: Hypothesis Testing and Interval
Estimation. **

These topics are at the heart of
the most widely used approach to statistical significance
testing and estimation.

**Chapter 9: Types of Errors and Power.**

A finding of statistical significance might be incorrect -- and
we probably would not know it. How likely are we to find
statistical significance if an effect is present? This
chapter introduces ways of thinking about that question.

**Chapter 10: One-Sample Tests and Estimates.**

We move from unrealistic statistics introduced in the previous
chapter to similar yet slightly more realistic analyses.

**Chapter 11: Two-Sample Tests and Estimates.**

This chapter introduces some statistics that commonly appear in
scientific journal articles.

**Chapter 12: Tests and Estimates for Two or More
Samples.**

As studies become more complex,
different statistics are needed. This chapter describes
one member of a family of common procedures (analysis of
variance), as well as some multiple comparison procedures.

**Chapter 13: Tests and Estimates for Bivariate
Linear Relationships.**

Building upon the
material in Chapter 5 on bivariate correlation, we now introduce
ways of using statistics to make linear predictions.

**Chapter 14: Analysis of Frequencies and Ranks.**

Statistics can be computed on frequencies within
categories. We explain some of the most common statistics
for this purpose, including the widely used odds ratio and
relative risk statistics, plus we explain why researchers
sometimes might want to use rank tests.

**Chapter 15: Choosing an Analysis Plan.**
We draw everything together in this chapter by leading the
reader through a series of questions to assess research
scenarios and choose from among the statistics covered in the
book.