Statistics - In a Nutshell : A Desktop Quick Reference

by Boslaugh, Sarah

• ISBN13: 9780596510497
• ISBN10: 0596510497
• Format: Paperback
• Copyright: 2008-07-01
• Publisher: Oreilly & Associates Inc

Summary

Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts.You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow 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.

Author Biography

Sarah Boslaugh holds a PhD in Research and Evaluation from the City University of New York and have been working as a statistical analyst for 15 years, in a variety of professional settings, including the New York City Board of Education, the Institutional Research Office of the City University of New York, Montefiore Medical Center, the Virginia Department of Social Services, Magellan Health Services, Washington University School of Medicine, and BJC HealthCare. She has taught statistics in several different contexts and currently teaches Intermediate Statistics at Washington University Medical School. She has published two previous books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE Publications, 2004) and Secondary Data Sources for Public Health (forthcoming from Cambridge U. Press, 2007) and am currently editing the Encyclopedia of Epidemiology for SAGE Publications (forthcoming, 2007).

Paul A. Watters PhD CITP, is Associate Professor in the School of Information and Mathematical Sciences and Centre for Informatics and Applied Optimization (CIAO) at the University of Ballarat. Until recently, he was Head of Data Services at the Medical Research Council's National Survey of Health and Development, which is the oldest of the British birth cohort studies, and an honorary senior research fellow at University College London. He uses multivariate statistics to develop orthogonal and non-orthogonal methods for feature extraction in pattern recognition, especially in biometric applications.

Table of Contents

Preface	p. xi
Basic Concepts of Measurement	p. 1
Measurement	p. 2
Levels of Measurement	p. 2
True and Error Scores	p. 7
Reliability and Validity	p. 8
Measurement Bias	p. 15
Exercises	p. 18
Probability	p. 21
About Formulas	p. 22
Basic Definitions	p. 23
Defining Probability	p. 29
Bayes's Theorem	p. 32
Enough Exposition, Let's Do Some Statistics!	p. 34
Exercises	p. 36
Data Management	p. 41
An Approach, Not a Set of Recipes	p. 42
The Chain of Command	p. 43
Codebooks	p. 43
The Rectangular Data File	p. 45
Spreadsheets and Relational Databases	p. 47
Inspecting a New Data File	p. 48
String and Numeric Data	p. 51
Missing Data	p. 51
Descriptive Statistics and Graphics	p. 54
Populations and Samples	p. 54
Measures of Central Tendency	p. 55
Measures of Dispersion	p. 58
Outliers	p. 62
Graphic Methods	p. 63
Bar Charts	p. 65
Bivariate Charts	p. 75
Exercises	p. 81
Research Design	p. 85
Observational Studies	p. 86
Experimental Studies	p. 88
Gathering Experimental Data	p. 90
Inference and Threats to Validity	p. 96
Eliminating Bias	p. 101
Example Experimental Design	p. 105
Critiquing Statistics Presented by Others	p. 107
The Misuse of Statistics	p. 107
Common Problems	p. 108
Quick Checklist	p. 110
Research Design	p. 111
Descriptive Statistics	p. 113
Inferential Statistics	p. 118
Inferential Statistics	p. 125
Probability Distributions	p. 126
Independent and Dependent Variables	p. 132
Populations and Samples	p. 133
The Central Limit Theorem	p. 137
Hypothesis Testing	p. 140
Confidence Intervals	p. 144
p-values	p. 145
Data Transformations	p. 146
Exercises	p. 149
The t-Test	p. 151
The t Distribution	p. 151
t-Tests	p. 152
One-Sample t-Test	p. 155
Two-Sample t-Test	p. 157
Repeated Measures t-Test	p. 160
Unequal Variance t-Test	p. 162
Effect Size and Power	p. 164
Exercises	p. 165
The Correlation Coefficient	p. 169
Measuring Association	p. 169
Graphing Associations Through Scatterplots	p. 170
Pearson's Product-Moment Correlation Coefficient	p. 176
Coefficient of Determination	p. 180
Spearman Rank-Order Coefficient	p. 183
Advanced Techniques	p. 185
Categorical Data	p. 188
The R x C Table	p. 189
The Chi-Square Distribution	p. 190
The Chi-Square Test	p. 191
Fisher's Exact Test	p. 196
McNemar's Test for Matched Pairs	p. 197
Correlation Statistics for Categorical Data	p. 199
The Likert and Semantic Differential Scales	p. 202
Exercises	p. 203
Nonparametric Statistics	p. 207
Nonnormal Data	p. 208
Between Subjects Designs	p. 209
Within-Subjects Designs	p. 217
Exercises	p. 221
Introduction to the General Linear Model	p. 224
The General Linear Model	p. 225
Linear Regression	p. 226
Analysis of Variance (ANOVA)	p. 232
Exercises	p. 239
Extensions of Analysis of Variance	p. 243
Factorial ANOVA	p. 244
MANOVA	p. 250
ANCOVA	p. 253
Repeated Measures ANOVA	p. 255
Mixed Designs	p. 257
Multiple Linear Regression	p. 264
Multiple Regression Models	p. 264
Common Problems with Multiple Regression	p. 277
Exercises	p. 279
Other Types of Regression	p. 284
Logistic Regression	p. 284
Logarithmic Transformations	p. 287
Polynomial Regression	p. 288
Overfitting	p. 292
Other Statistical Techniques	p. 298
Factor Analysis	p. 298
Cluster Analysis	p. 305
Discriminant Function Analysis	p. 309
Multidimensional Scaling	p. 312
Business and Quality Improvement Statistics	p. 315
Index Numbers	p. 315
Time Series	p. 319
Decision Analysis	p. 323
Quality Improvement	p. 328
Exercises	p. 335
Medical and Epidemiological Statistics	p. 339
Measures of Disease Frequency	p. 339
Ratio, Proportion, and Rate	p. 340
Prevalence and Incidence	p. 342
Crude, Category-Specific, and Standardized Rates	p. 345
The Risk Ratio	p. 348
The Odds Ratio	p. 352
Confounding, Stratified Analysis, and the Mantel-Haenszel Common Odds Ratio	p. 354
Power Analysis	p. 358
Sample Size Calculations	p. 361
Exercises	p. 362
Educational and Psychological Statistics	p. 366
Percentiles	p. 367
Standardized Scores	p. 369
Test Construction	p. 370
Classical Test Theory: The True Score Model	p. 373
Reliability of a Composite Test	p. 374
Measures of Internal Consistency	p. 375
Item Analysis	p. 379
Item Response Theory	p. 383
Exercises	p. 388
Review of Basic Mathematics	p. 391
Introduction to Statistical Packages	p. 414
References	p. 431
Index	p. 443
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