Key Features

  • Real-life local examples of health statistics are presented, e.g. A study conducted at the Department of Obstetrics and Gynecology, University of Utah School of Medicine, explored whether there might be a systematic bias affecting the results of genetic specimen tests, which could affect their generalizability.
  • Reader-friendly writing style
  • t-tests/ ANOVA family of inferential statistics all use variants of the same basic formula
  • Learning Objectives at the start of each chapter and Quick Reference Summaries at the end of each chapter provide the reader with a scope of the content within each chapter.

Table of Contents

Chapter 1: A Fool-Resistant Introduction to statistics

Chapter 2: Statistics as information

Chapter 3: Descriptive statistics

Chapter 4: Probability

Chapter 5: Inferential statistics, sampling and hypothesis testing

Chapter 6: Significance testing, beyond significance testing and experimental design

Chapter 7: Measures of differences (1): t-tests and the chi-square test

Chapter 8: Measures of differences (2): analysis of variance (ANOVA)

Chapter 9: Measures of association (1): correlation

Chapter 10: Measures of association (2): regression

Chapter 11: Qualitative research methods

Chapter 12: Statistics in the health sciences

Chapter 13: Reliability, validity and norms

Chapter 14: Statistics and the computer


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© 2013
Churchill Livingstone
Electronic ISBN:
Print ISBN:

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