Statistics in Context

Statistics in Context offers a fresh approach to teaching statistics. Designed to reduce students' fear of numbers, the text aims to put statistics-wary readers at ease with uncomplicated explanations and practical examples drawn from real research and everyday life. Written in lively, accessible prose, the narrative describes the who, what, when, where, and why, and also the how, of statistics.

DISTINCTIVE FEATURES

* "Everyday Statistics" boxes examine practical applications and relate them to the themes of the chapter
* "The Historical Context" features tell the story of how different statistical procedures developed
* "CheckPoint "exercises give students the chance to review the material and assess their understanding at the end of each section
* "Think About It" boxes challenge students to apply what they have learned to a difficult problem
* A variety of figures, tables, and worked examples guide students step by step through the calculations described in the text
* Abundant end-of-chapter practice problems give students many opportunities to test their mastery of the procedures described in the text
* The "Using Statistical Software" supplement teaches students how to perform statistical analysis using either SPSS or R

Barbara Blatchley is Professor of Psychology and Neuroscience at Agnes Scott College. She currently teaches courses in Research Statistics, Foundations of Neuroscience, and Sensation and Perception. Professor Blatchley is the author of numerous research articles in Biological Psychology and Neuroscience and several short essays on scientists during the Age of Enlightenment.

Chapter 1 Introduction: Statistics--Who Needs Them?
Chapter 2 Types of Data
Chapter 3 A Picture Is Worth a Thousand Words: Creating and Interpreting Graphics
Chapter 4 Measures of Central Tendency: What's So Average about the Mean?
Chapter 5 Variability: The "Law of Life"
Chapter 6 Where Am I? Normal Distributions and Standard Scores
Chapter 7 Basic Probability Theory
Chapter 8 The Central Limit Theorem and Hypothesis Testing
Chapter 9 The z-Test
Chapter 10 The t-Test
Chapter 11 Analysis of Variance
Chapter 12 Confidence Intervals and Effect Size: Building a Better Mousetrap
Chapter 13 Correlation and Regression: Are We Related?
Chapter 14 The Chi-Square Test
Chapter 15 Non-parametric Tests
Chapter 16 Which Test Should I Use and Why?