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. 

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