Intermediate Social Statistics: A Conceptual and Graphic Approach by Robert ArnoldIntermediate Social Statistics: A Conceptual and Graphic Approach by Robert Arnold

Intermediate Social Statistics: A Conceptual and Graphic Approach

byRobert Arnold

Paperback | December 12, 2014

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Offering a rich blend of accessible examples, illustrative graphics, and easy-to-follow instruction, Intermediate Social Statistics takes a conceptual approach to guide students through a broad range of statistical methods and ensure they understand both how to apply statistical techniques andwhy such techniques are used in the social sciences.
Robert Arnold worked for 13 years in applied research before becoming a university professor. He is currently an associate professor in the Department of Sociology, Anthropology, and Criminology at the University of Windsor. His primary area of interest is quantitative methodology and he has taught methods and statistics from the under...
Title:Intermediate Social Statistics: A Conceptual and Graphic ApproachFormat:PaperbackDimensions:352 pages, 9 × 7 × 0.64 inPublished:December 12, 2014Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199012075

ISBN - 13:9780199012077

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Table of Contents

Part One: Descriptive Statistics for One Variable1. Levels of MeasurementLearning ObjectivesThe Stevens ClassificationTwo Related ClassificationsGraphingSummaryReview Questions on Levels of MeasurementNotes2. Measures of Central TendencyLearning ObjectivesDefinitions and NotationLinks to Levels of MeasurementPotentially Unstable ResultsMeasures of Central Tendency as AveragesSummaryReview Questions on Central TendencyNotes3. Measures of DispersionLearning ObjectivesMeasures for Nominal VariablesQuantile-Based Measures of DispersionSummaryReview Questions on Measures of DispersionNotes4. Describing the Shape of a DistributionLearning ObjectivesModesSkewness and KurtosisFormulae for Skewness and KurtosisSummaryReview Questions on Shapes of DistributionsNotes5. Summarizing a DistributionLearning ObjectivesThe Five-Number SummaryGraphing a DistributionCreating a Mean and Standard Deviation TableSummaryReview Questions on Summarizing a DistributionPart Two: Statistical Inference6. Sampling DistributionsLearning ObjectivesThe Normal DistributionThe t DistributionThe Chi-Square DistributionRelations Among the Normal, t, and Chi-square DistributionsThe Effect of Sample SizeSummaryReview Questions on Sampling DistributionsNotes7. The Standard Model of Statistical InferenceLearning ObjectivesCentral IdeasSummaryReview Questions on the Standard Model of Statistical InferenceNote8. The Bayesian AlternativeLearning ObjectivesFrequentist and Personal ProbabilitiesBayes' TheoremEstimating a ProportionCredible IntervalsNumerical Equivalence to Standard ResultsSummaryReview Questions on the Bayesian AlternativeNotesPart Three: Measures of AssociationAssociation and Independence9. Measures for Nominal and Ordinal VariablesLearning ObjectivesPRE MeasuresThe Odds RatioSummaryReview Questions on Measures for Nominal and Ordinal VariablesNotes10. Pearson's rLearning ObjectivesExplaining the FormulaCorrelation MatricesGraphic Displays for Interval or Ratio DataSummaryReview Questions on Pearson's rNotexPart Four: Examining Crosstabulations11. Two-Way TablesLearning ObjectivesReading a CrosstabulationHeavy and Light CellsSetting Up a Crosstabulation for PresentationFurther Graphic Methods of Clarifying a CrosstabulationSummaryReview Questions on Heavy and Light Cells and Graphic MethodsNotes12. Conditional TablesLearning ObjectivesThe Columbia ApproachSpecificationCausal ChainsSpurious AssociationDistortionConditional ProbabilitiesAn Illustration with PolytomiesSummaryReview Questions on Conditional TablesNotesPart Five: Regression13. Bivariate RegressionLearning OutcomesOriginsThe Principle of Least SquaresThe Form of the EquationInterpreting bGraphic Display for Bivariate RegressionNon-linear TrendsSummaryReview Questions on Bivariate RegressionNotes14. Multiple RegressionLearning ObjectivesWhy Multiple Regression (MR)?Obtaining b's in Multiple RegressionInterpreting b's in Multiple RegressionGetting the Right Variables into the EquationInterpreting a Table of Regression ResultsInteraction TermsSetting Up a Regression TableGraphs Presenting Regression ResultsThe Special Case of Analysis of Variance (ANOVA)SummaryReview Questions on Multiple Regression and ANOVANotes15. Path AnalysisLearning ObjectivesA Famous Path ModelSetting Up Path DiagramsEquationsDecomposing a CorrelationSteps in Decomposing a CorrelationA Further ExampleSummaryReview Questions on Path AnalysisNotes16. Logistic RegressionLearning ObjectivesWhy Logistic Regression?LogitsInterpreting the b'sA Sample Logistic Regression TableAn Extension of the Logistic Model: Multinomial RegressionSummaryReview Questions on Logistic RegressionNotesAppendix A: Going a Step FurtherA1: Minimizing the Sum of Squared DeviationsA2: The Mean and Standard Deviation of Z-ScoresA3: The Standard Deviation of a ProportionAppendix B: Some Additional ExplanationsB1: Basic Notes on LogarithmsB2: Obtaining Expected Values for Chi-SquareB3: Another Form of Bayesian Hypothesis TestingGlossary of Statistical TermsCreditsReferencesIndex

Editorial Reviews

"I was impressed with the thorough approach. . . . Few books have as many examples completely worked out as this book does." --Kenneth MacKenzie, McGill University