Statistics in a Nutshell
A Desktop Quick Reference
Publisher: O'Reilly Media
Release Date: June 2009
Pages: 480
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You get a firm grasp of the fundamentals and a handson understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easytofollow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis.
Organized into four distinct sections, Statistics in a Nutshell offers you:

Introductory material:
 Different ways to think about statistics
 Basic concepts of measurement and probability theory
 Data management for statistical analysis
 Research design and experimental design
 How to critique statistics presented by others
 Basic concepts of inferential statistics
 The concept of correlation, when it is and is not an appropriate measure of association
 Dichotomous and categorical data
 The distinction between parametric and nonparametric statistics
 The General Linear Model
 Analysis of Variance (ANOVA) and MANOVA
 Multiple linear regression
 Business and quality improvement statistics
 Medical and public health statistics
 Educational and psychological statistics
Basic inferential statistics:
Advanced inferential techniques:
Specialized techniques:
Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to overemphasize calculation without teaching you when and how to apply different statistical tests.
With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.
Table of Contents

Chapter 1 Basic Concepts of Measurement

Measurement

Levels of Measurement

True and Error Scores

Reliability and Validity

Measurement Bias

Exercises


Chapter 2 Probability

About Formulas

Basic Definitions

Defining Probability

Bayes’s Theorem

Enough Exposition, Let’s Do Some Statistics!

Exercises


Chapter 3 Data Management

An Approach, Not a Set of Recipes

The Chain of Command

Codebooks

The Rectangular Data File

Spreadsheets and Relational Databases

Inspecting a New Data File

String and Numeric Data

Missing Data


Chapter 4 Descriptive Statistics and Graphics

Populations and Samples

Measures of Central Tendency

Measures of Dispersion

Outliers

Graphic Methods

Bar Charts

Bivariate Charts

Exercises


Chapter 5 Research Design

Observational Studies

Experimental Studies

Gathering Experimental Data

Inference and Threats to Validity

Eliminating Bias

Example Experimental Design


Chapter 6 Critiquing Statistics Presented by Others

The Misuse of Statistics

Common Problems

Quick Checklist

Research Design

Descriptive Statistics

Inferential Statistics


Chapter 7 Inferential Statistics

Probability Distributions

Independent and Dependent Variables

Populations and Samples

The Central Limit Theorem

Hypothesis Testing

Confidence Intervals

pvalues

Data Transformations

Exercises


Chapter 8 ThetTest

The t Distribution

tTests

OneSample tTest

TwoSample tTest

Repeated Measures tTest

Unequal Variance tTest

Effect Size and Power

Exercises


Chapter 9 The Correlation Coefficient

Measuring Association

Graphing Associations Through Scatterplots

Pearson’s ProductMoment Correlation Coefficient

Coefficient of Determination

Spearman RankOrder Coefficient

Advanced Techniques


Chapter 10 Categorical Data

The R×C Table

The ChiSquare Distribution

The ChiSquare Test

Fisher’s Exact Test

McNemar’s Test for Matched Pairs

Correlation Statistics for Categorical Data

The Likert and Semantic Differential Scales

Exercises


Chapter 11 Nonparametric Statistics

Nonnormal Data

Between Subjects Designs

WithinSubjects Designs

Exercises


Chapter 12 Introduction to the General Linear Model

The General Linear Model

Linear Regression

Analysis of Variance (ANOVA)

Exercises


Chapter 13 Extensions of Analysis of Variance

Factorial ANOVA

MANOVA

ANCOVA

Repeated Measures ANOVA

Mixed Designs


Chapter 14 Multiple Linear Regression

Multiple Regression Models

Common Problems with Multiple Regression

Exercises


Chapter 15 Other Types of Regression

Logistic Regression

Logarithmic Transformations

Polynomial Regression

Overfitting


Chapter 16 Other Statistical Techniques

Factor Analysis

Cluster Analysis

Discriminant Function Analysis

Multidimensional Scaling


Chapter 17 Business and Quality Improvement Statistics

Index Numbers

Time Series

Decision Analysis

Quality Improvement

Exercises


Chapter 18 Medical and Epidemiological Statistics

Measures of Disease Frequency

Ratio, Proportion, and Rate

Prevalence and Incidence

Crude, CategorySpecific, and Standardized Rates

The Risk Ratio

The Odds Ratio

Confounding, Stratified Analysis, and the MantelHaenszel Common Odds Ratio

Power Analysis

Sample Size Calculations

Exercises


Chapter 19 Educational and Psychological Statistics

Percentiles

Standardized Scores

Test Construction

Classical Test Theory: The True Score Model

Reliability of a Composite Test

Measures of Internal Consistency

Item Analysis

Item Response Theory

Exercises


Appendix Review of Basic Mathematics

Appendix Introduction to Statistical Packages

Appendix References

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