Statistics in a Nutshell [NOOK Book]

Overview

Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts.

Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform ...

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Statistics in a Nutshell

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Overview

Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts.

Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

  • Learn basic concepts of measurement and probability theory, data management, and research design
  • Discover basic statistical procedures, including correlation, the t-test, the chi-square and Fisher’s exact tests, and techniques for analyzing nonparametric data
  • Learn advanced techniques based on the general linear model, including ANOVA, ANCOVA, multiple linear regression, and logistic regression
  • Use and interpret statistics for business and quality improvement, medical and public health, and education and psychology
  • Communicate with statistics and critique statistical information presented by others
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Product Details

  • ISBN-13: 9781449361143
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 11/10/2012
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 2
  • Pages: 594
  • Sales rank: 527,153
  • File size: 19 MB
  • Note: This product may take a few minutes to download.

Meet the Author

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).

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Table of Contents


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