Simple Statistics: Applications in Social Research

Paperback | January 3, 2008

byTerance D. Miethe, Jane Florence Gauthier

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Simple Statistics provides a concise, compelling, and reasonably priced introduction to basic statistics for students of criminology and criminal justice. Written in a conversational tone, this text does not "dumb down" the material. Rather, it demonstrates the value of statistical thinkingand reasoning in context. For example, Chapter 2 illustrates the various ways that "garbage in, garbage out" affects the substantive conclusions drawn from statistical analyses. This book covers essential statistical techniques. It does not attempt to provide an encyclopedic sweep of all statistical procedures. Author Terance D. Miethe shows how verbal statements and other types of information are converted into statistical codes, measures, and variables. Many texts don'tcover this process of operationalization and measurement--so most students don't have a clue as to how research methods and statistics are related or how to conduct statistical analysis from the bottom up. This textbook provides answers to both "how to do..." and "why we do..." statistical procedures. Most statistics texts emphasize the "how to do..."--to the neglect of the "why we do..." questions. The problems at the end of each chapter focus on applications to provide more context for "why wedo..." these procedures. The term informed consumer is frequently used to convey the importance of understanding social statistics for becoming a better student, employee, and citizen. The book uses hand computation methods to demonstrate how to apply the various statistical procedures. Most chapters also contain an optional section on how to do these procedures in SPSS and/or Microsoft Excel spreadsheets. But such applications are not necessary for understanding the statisticalmethods described in this book. Several examples are used to illustrate each statistical procedure to help students understand and apply them. However, rather than overwhelming students with too many examples, the book offers a balance between computation methods and examples of how to do them. Specific problems, detailed summaries, key terms, and major formulas are provided at the end of each chapter to further highlight major points. A comprehensive Instructor's Manual, written by Miethe, is available.

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Simple Statistics provides a concise, compelling, and reasonably priced introduction to basic statistics for students of criminology and criminal justice. Written in a conversational tone, this text does not "dumb down" the material. Rather, it demonstrates the value of statistical thinkingand reasoning in context. For example, Chapter...

Terance D. Miethe is Professor of Criminal Justice at the University of Nevada, Las Vegas. He is author of Simple Statistics: Applications in Criminology and Criminal Justice (OUP, 2006) and coauthor of many books, including Crime Profiles: The Anatomy of Dangerous Persons, Places, and Situations (OUP, 2005). Jane Florence Gauthier is...

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Format:PaperbackDimensions:352 pages, 9.2 × 6.9 × 0.8 inPublished:January 3, 2008Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195332547

ISBN - 13:9780195332544

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Extra Content

Table of Contents

CHAPTER 1: INTRODUCTION TO STATISTICAL THINKINGCHAPTER 2: GARBAGE IN, GARBAGE OUTMeasurement InvaliditySampling ProblemsFaulty Causal InferencesPolitical InfluencesHuman FallibilityCHAPTER 3: ISSUES IN DATA PREPARATIONWhy Is Data Preparation Important?Operationalization and MeasurementNominal Measurement of Qualitative VariablesMeasurement of Quantitative VariablesIssues in Levels of MeasurementCoding and Inputting Statistical DataAvailable Computer Software for Basic Data AnalysisCHAPTER 4: DISPLAYING DATA IN TABLES AND GRAPHIC FORMSThe Importance of Data Tables and GraphsTypes of Tabular and Visual PresentationsTables and Graphs for Qualitative VariablesTables and Graphs for Quantitative VariablesRatios and RatesMaps of Qualitative and Quantitative VariablesHazards and Distortions in Visual Displays and Collapsing CategoriesCHAPTER 5: MODES, MEDIANS, MEANS, AND MOREModes and Modal CategoriesThe Median and Other Measures of LocationThe Mean and Its MeaningWeighted MeansStrengths and Limitations of Mean RatingsChoice of Measure of Central Tendency and PositionCHAPTER 6: MEASURES OF VARIATION AND DISPERSIONThe Range of ScoresThe Variance and Standard DeviationVariances and Standard Deviations for Binary VariablesPopulation versus Sample Variances and Standard DeviationsCHAPTER 7: THE NORMAL CURVE AND SAMPLING DISTRIBUTIONSThe Normal CurveZ-Scores as Standard ScoresReading a Normal Curve TableOther Sampling DistributionsBinomial Distributiont-DistributionChi-Square DistributionF-DistributionCHAPTER 8: PARAMETER ESTIMATION AND CONFIDENCE INTERVALSSampling Distributions and the Logic of Parameter EstimationInferences from Sampling Distributions to One Real SampleConfidence Intervals: Large Samples, ? KnownConfidence Intervals for Population MeansConfidence Intervals for PopulationProportionsConfidence Intervals: Small Samples and Unknown ?Properties of the t-DistributionConfidence Intervals for Population Means for Unknown ?Confidence Intervals for PopulationProportion for Unknown ?CHAPTER 9: INTRODUCTION TO HYPOTHESIS TESTINGConfidence Intervals Versus Hypothesis TestingBasic Terminology and SymbolsTypes of HypothesesZone of Rejection and Critical ValuesSignificance Levels and Errors in Decision-MakingCHAPTER 10: HYPOTHESIS TESTING FOR MEANS AND PROPORTIONSTypes of Hypothesis TestingOne-Sample Tests of the Population MeanOne-Sample Tests of a Population ProportionTwo Sample Test of Differences in Population MeansTwo Sample Tests of Differences in Population ProportionsIssues in Testing Statistical HypothesesCHAPTER 11: STATISTICAL ASSOCIATION IN CONTINGENCY TABLESThe Importance of Statistical Association and Contingency TablesThe Structure of a Contingency TableDeveloping Tables of Total, Row, and Column PercentagesThe Rules for Interpreting a Contingency TableSpecifying Causal Relations in Contingency TablesAssessing the Magnitude of BivariateAssociations in Contingency TablesVisual and Intuitive ApproachThe Chi-Square Test of Statistical IndependenceIssues in Contingency Table AnalysisHow Many Categories for Categorical Variables?GIGO and the Value of Theory in Identifying VariablesSample Size and Significance TestsOther Measures of Association for Categorical VariablesCHAPTER 12: THE ANALYSIS OF VARIANCE (ANOVA)Overview of ANOVA and When it is UsedPartitioning Variation into Between and Within Group DifferencesCalculating the Total Variation in a Dependent VariableCalculating the Between-Group VariationCalculating the Within-Group VariationHypothesis Testing and Measures of Association in ANOVATesting the Hypothesis of Equality of Group MeansMeasures of Association in ANOVAIssues in the Analysis of VarianceCHAPTER 13: CORRELATION AND REGRESSIONThe Scatterplot of Two Interval/Ratio VariablesThe Correlation CoefficientRegression AnalysisThe Computation of the RegressionCoefficient and Y-InterceptGoodness of Fit of a Regression EquationHypothesis Testing and Tests of Statistical SignificanceUsing Regression Analysis for Predicting OutcomesIssues in Bivariate Regression and Correlation AnalysiCHAPTER 14: INTRODUCTION TO MULTIVARIATE ANALYSISWhy Do Multivariate Analysis?Exploring Multiple CausesStatistical ControlTypes of Multivariate AnalysisMultivariate Contingency Table AnalysisPartial Correlation CoefficientsMultiple Regression Analysis

Editorial Reviews

"Throughout this book, the author explains the relevance of statistical techniques--not just the mechanics. The conversational style is engaging, encouraging students to keep reading and realize that they can master statistics. The book distinguishes itself from other texts by paring down whatstudents are expected to learn."--Wayne J. Pitts, University of Memphis