Statistics in a Nutshell (In a Nutshell (O'Reilly) Series) / Edition 1

Statistics in a Nutshell (In a Nutshell (O'Reilly) Series) / Edition 1

by Sarah Boslaugh, Paul Andrew, Dr. Watters Dr.
     
 

A clear and concise introduction and reference, this work gives readers a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts.See more details below

Overview

A clear and concise introduction and reference, this work gives readers a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts.

Product Details

ISBN-13:
9780596510497
Publisher:
O'Reilly Media, Incorporated
Publication date:
07/01/2008
Series:
In a Nutshell (O'Reilly) Series
Pages:
480
Sales rank:
1,267,174
Product dimensions:
6.00(w) x 8.90(h) x 1.20(d)

Related Subjects

Table of Contents

Preface;
Chapter 1: Basic Concepts of Measurement;
1.1 Measurement;
1.2 Levels of Measurement;
1.3 True and Error Scores;
1.4 Reliability and Validity;
1.5 Measurement Bias;
1.6 Exercises;
Chapter 2: Probability;
2.1 About Formulas;
2.2 Basic Definitions;
2.3 Defining Probability;
2.4 Bayes’s Theorem;
2.5 Enough Exposition, Let’s Do Some Statistics!;
2.6 Exercises;
Chapter 3: Data Management;
3.1 An Approach, Not a Set of Recipes;
3.2 The Chain of Command;
3.3 Codebooks;
3.4 The Rectangular Data File;
3.5 Spreadsheets and Relational Databases;
3.6 Inspecting a New Data File;
3.7 String and Numeric Data;
3.8 Missing Data;
Chapter 4: Descriptive Statistics and Graphics;
4.1 Populations and Samples;
4.2 Measures of Central Tendency;
4.3 Measures of Dispersion;
4.4 Outliers;
4.5 Graphic Methods;
4.6 Bar Charts;
4.7 Bivariate Charts;
4.8 Exercises;
Chapter 5: Research Design;
5.1 Observational Studies;
5.2 Experimental Studies;
5.3 Gathering Experimental Data;
5.4 Inference and Threats to Validity;
5.5 Eliminating Bias;
5.6 Example Experimental Design;
Chapter 6: Critiquing Statistics Presented by Others;
6.1 The Misuse of Statistics;
6.2 Common Problems;
6.3 Quick Checklist;
6.4 Research Design;
6.5 Descriptive Statistics;
6.6 Inferential Statistics;
Chapter 7: Inferential Statistics;
7.1 Probability Distributions;
7.2 Independent and Dependent Variables;
7.3 Populations and Samples;
7.4 The Central Limit Theorem;
7.5 Hypothesis Testing;
7.6 Confidence Intervals;
7.7 p-values;
7.8 Data Transformations;
7.9 Exercises;
Chapter 8: Thet-Test;
8.1 The t Distribution;
8.2 t-Tests;
8.3 One-Sample t-Test;
8.4 Two-Sample t-Test;
8.5 Repeated Measures t-Test;
8.6 Unequal Variance t-Test;
8.7 Effect Size and Power;
8.8 Exercises;
Chapter 9: The Correlation Coefficient;
9.1 Measuring Association;
9.2 Graphing Associations Through Scatterplots;
9.3 Pearson’s Product-Moment Correlation Coefficient;
9.4 Coefficient of Determination;
9.5 Spearman Rank-Order Coefficient;
9.6 Advanced Techniques;
Chapter 10: Categorical Data;
10.1 The R×C Table;
10.2 The Chi-Square Distribution;
10.3 The Chi-Square Test;
10.4 Fisher’s Exact Test;
10.5 McNemar’s Test for Matched Pairs;
10.6 Correlation Statistics for Categorical Data;
10.7 The Likert and Semantic Differential Scales;
10.8 Exercises;
Chapter 11: Nonparametric Statistics;
11.1 Nonnormal Data;
11.2 Between Subjects Designs;
11.3 Within-Subjects Designs;
11.4 Exercises;
Chapter 12: Introduction to the General Linear Model;
12.1 The General Linear Model;
12.2 Linear Regression;
12.3 Analysis of Variance (ANOVA);
12.4 Exercises;
Chapter 13: Extensions of Analysis of Variance;
13.1 Factorial ANOVA;
13.2 MANOVA;
13.3 ANCOVA;
13.4 Repeated Measures ANOVA;
13.5 Mixed Designs;
Chapter 14: Multiple Linear Regression;
14.1 Multiple Regression Models;
14.2 Common Problems with Multiple Regression;
14.3 Exercises;
Chapter 15: Other Types of Regression;
15.1 Logistic Regression;
15.2 Logarithmic Transformations;
15.3 Polynomial Regression;
15.4 Overfitting;
Chapter 16: Other Statistical Techniques;
16.1 Factor Analysis;
16.2 Cluster Analysis;
16.3 Discriminant Function Analysis;
16.4 Multidimensional Scaling;
Chapter 17: Business and Quality Improvement Statistics;
17.1 Index Numbers;
17.2 Time Series;
17.3 Decision Analysis;
17.4 Quality Improvement;
17.5 Exercises;
Chapter 18: Medical and Epidemiological Statistics;
18.1 Measures of Disease Frequency;
18.2 Ratio, Proportion, and Rate;
18.3 Prevalence and Incidence;
18.4 Crude, Category-Specific, and Standardized Rates;
18.5 The Risk Ratio;
18.6 The Odds Ratio;
18.7 Confounding, Stratified Analysis, and the Mantel-Haenszel Common Odds Ratio;
18.8 Power Analysis;
18.9 Sample Size Calculations;
18.10 Exercises;
Chapter 19: Educational and Psychological Statistics;
19.1 Percentiles;
19.2 Standardized Scores;
19.3 Test Construction;
19.4 Classical Test Theory: The True Score Model;
19.5 Reliability of a Composite Test;
19.6 Measures of Internal Consistency;
19.7 Item Analysis;
19.8 Item Response Theory;
19.9 Exercises;
Review of Basic Mathematics;
Introduction to Statistical Packages;
References;
Colophon;

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