An Introduction to Statistics in Psychology:

An Introduction to Statistics in Psychology is the simplest approach to the wide range of elementary, intermediate and advanced statistics needed by undergraduate (and postgraduate) students in Psychology. It is designed to meet their needs at all stages in their studies. Together with the Guide to Computing Statistics with SPSS for Windows, the book provides a complete package aiding students not only to select and compute appropriate tests for their data, but also to interpret the statistics and report their findings.
This comprehensive text is written in an accessible and jargon free way. Short chapters ensure its suitability for modular study by allowing the instructor to tailor the material to their students needs.
Complex mathematics is kept to a minimum and concepts that are often difficult to grasp are explained step-by-step using a wide variety of examples.

Duncan Cramer is Reader in Psychology at the Department of Social Sciences at the University of Loughborough.

Introduction
Why You Need Statistics
Describing Variables
Tables and Diagrams
Describing Variables Numerically
Averages, Variation and Spread
Shapes of Distributions of Scores
Standard Deviations
The Standard Unit of Measurement in Statistics
Relationships Between Two or More Variables
Diagrams and Tables
Correlation Coefficients
Pearson Correlation and Spearman's Rho
Regression
Prediction with Precision
Samples and Populations
Generalising and Inferring
Statistical Significance for the Correlation Coefficient
A Practical Introduction to Statistical Inference
Standard Error: The Standard Deviation of the Means of Samples
T-Test: Comparing Two Samples of Correlated/Related Scores
The T-Test: Comparing Two Groups of Unrelated/Uncorrelated Scores
Chi-Squared Differences Between Samples of Frequency Data
Probity
Reporting Significance Levels Succintly
One-Tabled versus Two-Tabled Significance Testing
Ranking Tests: Non-Parametric Statistics
The Varience Ratio Test
The F Ratio to Compare Two Variances
Analysis of Variance (ANOVA)
Introduction to the One-Way Unrelated or Uncorrelated Anova
Analysis of Variance for Correlated Scores or Repeated Measures
Two-Way Analysis of Variations for Unrelated/Uncorrelated Scores
Two Experiments for the Price of One? Multiple Comparisons in ANOVA
Just Where do the Differences Lie? More on the Analysis of Variance (ANOVA)
Special Variants of the Approach
Statistics and the Analysis of Experiments
Partial Correlation
Spurious Correlation
Third Variables
Suppressor Variables
Factor Analysis
Simplifying Complex Data
Multiple Regression and Multiple Correlation
Path Analysis
The Analysis of a Questionnaire/Survey Project
Statistical Power Analysis
Do My Findings Matter?
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An Introduction to Statistics in Psychology: A Complete Guide for Students

Summary

Author Biography

Table of Contents

Supplemental Materials