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# Statistics Explained : Guide for Social Science Students - 2nd edition

## ISBN10: 0415332850

Edition: 2ND 04
Publisher: Routledge N. Y.
Published: 2004
International: No

## ISBN10: 0415332850

Edition: 2ND 04

### Summary

Do you need help with statistics? Are you confused by the wide range of statistical tests and their uses?

Statistics Explained, Second Edition clearly outlines the major statistical tests used by undergraduates in psychology and the social sciences. It provides easy-to-understand explanations of how and why they are used and makes statistics much less of a burden. This book:

• is a simple introduction to statistical concepts and ideas
• shows you when to be sceptical about statistics
• helps you to understand the results of statistical analysis by computer.

Expanding and revising the best-selling first edition, the author has included new material which throws light on the mysteries of the general linear model, power, reliability and factor analysis, whilst other areas have been fully up-dated. Unobtrusive cross-referencing makes this the ideal companion to SPSS Explained, also published by Routledge.

Statistics Explained, Second Edition can be dipped into so that readers can see why a specific analytical procedure was developed and what it is best used for. Readers can also analyse their own data by following the worked examples provided.

Preface.

Introduction.

Descriptive Statistics.

Standard Scores.

Introduction to Hypothesis Testing.

Sampling.

Hypothesis Testing with One Sample.

Selecting Samples for Comparison.

Hypothesis Testing with Two Samples.

Statistical Power.

Introduction to the Analysis of Variance.

One Factor Independent Measures ANOVA.

Multiple Comparisons.

One Factor Repeated Measures ANOVA.

The Interaction of Factors in the Analysis of Variance.

Calculating the Two Factor ANOVA.

Introduction to Nonparametric Analysis.

Two Sample Nonparametric Analyses.

One Factor ANOVA for Ranked Data.

Analyzing Frequency Data : Chi-Square.

Linear Correlation and Regression.

Multiple Correlation and Regression.

Complex Analyses and Computers.

An Introduction to the General Linear Model.

Notes.

References.

Appendix: Statistical Tables.