H. Russell Bernard is Director of the Institute for Social Science Research at Arizona State University and Professor Emeritus of Anthropology at the University of Florida. He is the author of Social Research Methods, third edition, Analyzing Qualitative Data: Systematic Approaches, second edition, and Native Ethnography.Amber Wutich is Director of the Center for Global Health and Associate Director of the Institute for Social Science Research at Arizona State University. She is the author of Social Research Methods, third edition, and The Human Story: An Introduction to Anthropology, Lazy Crazy, and Disgusting: Stigma and the Undoing of Global Health, and Analyzing Qualitative Data: Systematic Approaches, second edition.

In my courses on ethnographic methods, I have assigned multiple incarnations of H. Russell Bernard’s Research Methods in Anthropology to upper-division undergraduate and graduate students. I also use it as my own go-to guide for planning and implementing anthropological projects. The latest edition, co-authored with Amber Wutich, includes substantial additional guidance on writing proposals and drafting publications. It also contains expanded and updated material on research ethics and clarification on important qualitative methods. I look forward to assigning this updated book in the near future.

• Chapter 1: Anthropology and the Social SciencesIntroductionMethods Belong to All of UsThe Many Meanings of MethodRationalism, Empiricism, and MoralityThe Norms of ScienceThe Development of Science—From Democritus to NewtonExploration, Printing, and Modern ScienceScience, Money, and WarThe Development of Social Science—From Newton to RousseauEarly Positivism: Quételet, Saint-Simon, ComteGreat Failures in Science and Social ScienceThe Varieties of PositivismLater Positivism: The Vienna CircleInstrumental PositivismThe Reaction against PositivismAnd Finally … The Qualitative/Quantitative SplitChapter 2: The Foundations of Social ResearchIntroductionVariables: The Joy of MeasurementMeasurement and ConceptsConceptual and Operational DefinitionsConceptual DefinitionsOperational DefinitionsLevels of MeasurementReliability, Validity, Accuracy, and PrecisionDetermining ValidityUnits of AnalysisChapter 3: Preparing for ResearchIntroduction—Setting Things UpThe Ideal Research ProcessA Realistic ApproachAlternative Paradigms for Building TheoriesChoosing a Research Problem: A Guide to Research Topics, AnywayMeta-analysisChapter 4: Research DesignIntroduction: What Is Research Design?Cause and EffectThree Decisions in Research DesignThe Eight Types of Research DesignThe Components of a Research DesignThe Art of Proposal WritingHow to Develop Your Proposal with Mentors and PeersChapter 5: Experiments and Experimental ThinkingIntroductionKinds of Confounds: Threats to Internal Validity Controlling for Threats to ValidityField ExperimentsAre Field Experiments Ethical?Thought ExperimentsChapter 6: Ethics and the Conduct of AnthropologyIntroductionI: Choosing a Research ProblemII: Making Our Work Less Extractive and ExploitativeParticipatory and Action ResearchIII: Getting Informed ConsentHow to Get Your IRB Proposal ApprovedIV: Maintaining ConfidentialityChapter 7: Probability Sampling Introduction: What Are Samples and Why Do We Need Them?Sampling FramesStratified SamplingCluster Sampling and Complex Sampling DesignsMaximizing Between-group Variance: The Wichita StudyHow Big Should a Sample Be?The Normal Distribution and z-scoresThe Central Limit TheoremThe Standard Error and Confidence IntervalsCalculating Sample Size for Estimating MeansCalculating Sample Size for Estimating ProportionsChapter 8: Nonprobability Sampling Introduction: Reasons to Use a Nonprobability SampleFour Common and Two Uncommon Types of Nonprobability SamplesMinimum Sizes for Different Types of Nonprobability SamplesDeciding on a Nonprobability Sampling Method and Sample SizeAnd Finally . . .Chapter 9: Interviewing and Focus GroupsIntroduction—The Big PictureInterview ControlUnstructured InterviewingProbingLearning to InterviewPositionality and Presentation of SelfUsing a Voice RecorderUsing Visual Cues, Like Photos in InterviewsFocus GroupsResponse EffectsInformant/Respondent AccuracyChapter 10: QuestionnairesIntroductionPersonal, Face-to-face InterviewsTelephone InterviewsSelf-administered QuestionnairesWhen to Use WhatWorking with InterviewersClosed- versus Open-ended QuestionsFourteen Rules for Question Wording and FormatPretesting and Learning from MistakesTranslation and Back TranslationThe Response Rate ProblemImproving Response Rates: The Legacy of Dillman’s Total Design MethodCross-sectional and Longitudinal StudiesSome Specialized Survey MethodsAnd FinallyChapter 11: Collecting Cultural Domain DataIntroductionIt Started with the Domain of KinshipFree ListingThe True–False/Yes–No and Sentence Frame TechniquesTriad TestsFree Pile SortsRankings and Paired ComparisonsChapter 12: Collecting Social Network DataIntroduction—What Is Social Network Analysis?Anthropology and Social Network AnalysisWhole NetworksPersonal NetworksDoing Network AnalysisCollecting Whole (Sociocentric) Network DataMethods for Finding Network TiesCollecting Personal (Egocentric) Network DataReducing Respondent BurdenChapter 13: Scales and ScalingIntroductionSingle-question ScalesIndexesGuttman ScalesSome Examples of a Guttman ScaleLikert ScalesItem AnalysisTesting for Unidimensionality with Factor AnalysisThe Semantic DifferentialChapter 14: Participant ObservationIntroductionWhat Is Participant Observation?The Stages of Participant ObservationEntering the FieldFieldwork RolesThe Skills of a Participant ObserverBuilding Explicit AwarenessEthically Practicing the Darker Arts of FieldworkObjectivityStudying Your Own CultureRapid AssessmentValidity—AgainSurviving FieldworkChapter 15: Field Notes and Data ManagementIntroductionHow to Write Field NotesField NotesCoding Field NotesAnalyzing Field NotesDatabase ManagementChapter 16: Direct ObservationIntroductionCM—Continuous MonitoringCoding SchemesSpot Sampling and Time Allocation StudiesExperience Sampling (ES) and Ecological Momentary Assessment (EMA)Unobtrusive ObservationIndirect ObservationArchival ResearchChapter 17: Introduction to Data AnalysisIntroduction: Qualitative, QuantitativeData MatricesPresenting Results in Matrices and TablesPresenting Results: Causal Flow ChartsChapter 18: Analyzing Cultural Domain DataIntroductionAnalyzing Free ListsAnalyzing Pile Sort DataHow MDS WorksCluster Analysis and Pile Sort DataHow Cluster Analysis WorksA Real Research Example: Green Behavior and Electric Cars in the United StatesAnalyzing Triad DataAnalyzing Sentence FramesAnalyzing Paired ComparisonsCultural Consensus AnalysisRunning Consensus AnalysisCultural ConsonanceCultural Domains and Folk TaxonomiesChapter 19: Analyzing Network DataIntroduction: A Bit More About MatricesAnalyzing Social Network DataAnalyzing Whole (Sociocentric) Network DataAnalyzing Personal (Egocentric) Network Data“It’s Not What You Know, It’s Who You Know”Adding Network Data to the Classic RecipeAffiliation MatricesSemantic NetworksChapter 20: Analyzing Text I: Theme Coding, Grounded Theory, and Content AnalysisIntroductionOverview of Grounded TheoryContent AnalysisDoing Classical Content AnalysisIntercoder ReliabilityAI and Text AnalysisHRAF: Cross-cultural Content AnalysisDoing Cross-cultural Text-based ResearchChapter 21: Analyzing Text II: Discourse Analysis IntroductionConversation AnalysisTaking Turns in a JuryNarrative AnalysisPhenomenological Analysis of NarrativesLanguage in UseCritical Discourse Analysis: Language and PowerChapter 22: Text Analysis III: Analytic LogicIntroductionEthnographic Decision Models (EDM)Representing Complicated Models with Tables and IF?THEN ChartsSchema AnalysisThree Examples of Schema AnalysisAnalytic Induction/Qualitative Comparative AnalysisQualitative Comparative Analysis—QCAAnd Finally . . .Chapter 23: Univariate and Bivariate AnalysisIntroductionUnivariate Analysis: Raw DataFrequency DistributionsMeasures of Central TendencyVisualizing DataMeasures of Variation I: Range and Interquartile RangeMeasures of Variation II: Variance and the Standard DeviationThe Logic of Hypothesis TestingSo, What About the Mean of FEMILLIT?More About z-ScoresThe Univariate Chi-square TestTesting Relations: Bivariate AnalysisThe t-Test: Comparing Two MeansANOVA—Analysis of VarianceExamples of ANOVAVisualizing the Direction and Shape of CovariationsCrosstabs of Nominal VariablesCorrelation and Cause: Antecedent and Intervening VariablesChi-square for Bivariate ComparisonsTesting the Association Between Ordinal VariablesWhat to Use for Nominal and Ordinal VariablesCorrelation: The Powerhouse Statistic for CovariationSpearman’s rPearson’s rRegressionHow Regression WorksTesting the Significance of rNonlinear RelationsStatistical Significance, the Shotgun Approach, and Other IssuesChapter 24: Multivariate Analysis IntroductionElaboration: Controlling for Independent VariablesCar Wrecks and Teenage BirthsThe Multiple Regression EquationUnraveling the Teenage-birth-and-motor-vehicle-death PuzzlePath AnalysisFactor AnalysisDiscriminant Function Analysis (DFA)And Finally . . .Chapter 25: On Writing UpIntroductionGetting Your Article PublishedAppendix A: Table of Areas under a Normal Curve Appendix B: Student’s t Distribution Appendix C: Chi-square Distribution Table Appendix D: F Table for the .05 Level of Significance Appendix E: Resources for FieldworkersReferences

H. Russell Bernard is Director of the Institute for Social Science Research at Arizona State University and Professor Emeritus of Anthropology at the University of Florida. He is the author of Social Research Methods, third edition, Analyzing Qualitative Data: Systematic Approaches, second edition, and Native Ethnography.Amber Wutich is Director of the Center for Global Health and Associate Director of the Institute for Social Science Research at Arizona State University. She is the author of Social Research Methods, third edition, and The Human Story: An Introduction to Anthropology, Lazy Crazy, and Disgusting: Stigma and the Undoing of Global Health, and Analyzing Qualitative Data: Systematic Approaches, second edition.

In my courses on ethnographic methods, I have assigned multiple incarnations of H. Russell Bernard’s Research Methods in Anthropology to upper-division undergraduate and graduate students. I also use it as my own go-to guide for planning and implementing anthropological projects. The latest edition, co-authored with Amber Wutich, includes substantial additional guidance on writing proposals and drafting publications. It also contains expanded and updated material on research ethics and clarification on important qualitative methods. I look forward to assigning this updated book in the near future.

• Chapter 1: Anthropology and the Social SciencesIntroductionMethods Belong to All of UsThe Many Meanings of MethodRationalism, Empiricism, and MoralityThe Norms of ScienceThe Development of Science—From Democritus to NewtonExploration, Printing, and Modern ScienceScience, Money, and WarThe Development of Social Science—From Newton to RousseauEarly Positivism: Quételet, Saint-Simon, ComteGreat Failures in Science and Social ScienceThe Varieties of PositivismLater Positivism: The Vienna CircleInstrumental PositivismThe Reaction against PositivismAnd Finally … The Qualitative/Quantitative SplitChapter 2: The Foundations of Social ResearchIntroductionVariables: The Joy of MeasurementMeasurement and ConceptsConceptual and Operational DefinitionsConceptual DefinitionsOperational DefinitionsLevels of MeasurementReliability, Validity, Accuracy, and PrecisionDetermining ValidityUnits of AnalysisChapter 3: Preparing for ResearchIntroduction—Setting Things UpThe Ideal Research ProcessA Realistic ApproachAlternative Paradigms for Building TheoriesChoosing a Research Problem: A Guide to Research Topics, AnywayMeta-analysisChapter 4: Research DesignIntroduction: What Is Research Design?Cause and EffectThree Decisions in Research DesignThe Eight Types of Research DesignThe Components of a Research DesignThe Art of Proposal WritingHow to Develop Your Proposal with Mentors and PeersChapter 5: Experiments and Experimental ThinkingIntroductionKinds of Confounds: Threats to Internal Validity Controlling for Threats to ValidityField ExperimentsAre Field Experiments Ethical?Thought ExperimentsChapter 6: Ethics and the Conduct of AnthropologyIntroductionI: Choosing a Research ProblemII: Making Our Work Less Extractive and ExploitativeParticipatory and Action ResearchIII: Getting Informed ConsentHow to Get Your IRB Proposal ApprovedIV: Maintaining ConfidentialityChapter 7: Probability Sampling Introduction: What Are Samples and Why Do We Need Them?Sampling FramesStratified SamplingCluster Sampling and Complex Sampling DesignsMaximizing Between-group Variance: The Wichita StudyHow Big Should a Sample Be?The Normal Distribution and z-scoresThe Central Limit TheoremThe Standard Error and Confidence IntervalsCalculating Sample Size for Estimating MeansCalculating Sample Size for Estimating ProportionsChapter 8: Nonprobability Sampling Introduction: Reasons to Use a Nonprobability SampleFour Common and Two Uncommon Types of Nonprobability SamplesMinimum Sizes for Different Types of Nonprobability SamplesDeciding on a Nonprobability Sampling Method and Sample SizeAnd Finally . . .Chapter 9: Interviewing and Focus GroupsIntroduction—The Big PictureInterview ControlUnstructured InterviewingProbingLearning to InterviewPositionality and Presentation of SelfUsing a Voice RecorderUsing Visual Cues, Like Photos in InterviewsFocus GroupsResponse EffectsInformant/Respondent AccuracyChapter 10: QuestionnairesIntroductionPersonal, Face-to-face InterviewsTelephone InterviewsSelf-administered QuestionnairesWhen to Use WhatWorking with InterviewersClosed- versus Open-ended QuestionsFourteen Rules for Question Wording and FormatPretesting and Learning from MistakesTranslation and Back TranslationThe Response Rate ProblemImproving Response Rates: The Legacy of Dillman’s Total Design MethodCross-sectional and Longitudinal StudiesSome Specialized Survey MethodsAnd FinallyChapter 11: Collecting Cultural Domain DataIntroductionIt Started with the Domain of KinshipFree ListingThe True–False/Yes–No and Sentence Frame TechniquesTriad TestsFree Pile SortsRankings and Paired ComparisonsChapter 12: Collecting Social Network DataIntroduction—What Is Social Network Analysis?Anthropology and Social Network AnalysisWhole NetworksPersonal NetworksDoing Network AnalysisCollecting Whole (Sociocentric) Network DataMethods for Finding Network TiesCollecting Personal (Egocentric) Network DataReducing Respondent BurdenChapter 13: Scales and ScalingIntroductionSingle-question ScalesIndexesGuttman ScalesSome Examples of a Guttman ScaleLikert ScalesItem AnalysisTesting for Unidimensionality with Factor AnalysisThe Semantic DifferentialChapter 14: Participant ObservationIntroductionWhat Is Participant Observation?The Stages of Participant ObservationEntering the FieldFieldwork RolesThe Skills of a Participant ObserverBuilding Explicit AwarenessEthically Practicing the Darker Arts of FieldworkObjectivityStudying Your Own CultureRapid AssessmentValidity—AgainSurviving FieldworkChapter 15: Field Notes and Data ManagementIntroductionHow to Write Field NotesField NotesCoding Field NotesAnalyzing Field NotesDatabase ManagementChapter 16: Direct ObservationIntroductionCM—Continuous MonitoringCoding SchemesSpot Sampling and Time Allocation StudiesExperience Sampling (ES) and Ecological Momentary Assessment (EMA)Unobtrusive ObservationIndirect ObservationArchival ResearchChapter 17: Introduction to Data AnalysisIntroduction: Qualitative, QuantitativeData MatricesPresenting Results in Matrices and TablesPresenting Results: Causal Flow ChartsChapter 18: Analyzing Cultural Domain DataIntroductionAnalyzing Free ListsAnalyzing Pile Sort DataHow MDS WorksCluster Analysis and Pile Sort DataHow Cluster Analysis WorksA Real Research Example: Green Behavior and Electric Cars in the United StatesAnalyzing Triad DataAnalyzing Sentence FramesAnalyzing Paired ComparisonsCultural Consensus AnalysisRunning Consensus AnalysisCultural ConsonanceCultural Domains and Folk TaxonomiesChapter 19: Analyzing Network DataIntroduction: A Bit More About MatricesAnalyzing Social Network DataAnalyzing Whole (Sociocentric) Network DataAnalyzing Personal (Egocentric) Network Data“It’s Not What You Know, It’s Who You Know”Adding Network Data to the Classic RecipeAffiliation MatricesSemantic NetworksChapter 20: Analyzing Text I: Theme Coding, Grounded Theory, and Content AnalysisIntroductionOverview of Grounded TheoryContent AnalysisDoing Classical Content AnalysisIntercoder ReliabilityAI and Text AnalysisHRAF: Cross-cultural Content AnalysisDoing Cross-cultural Text-based ResearchChapter 21: Analyzing Text II: Discourse Analysis IntroductionConversation AnalysisTaking Turns in a JuryNarrative AnalysisPhenomenological Analysis of NarrativesLanguage in UseCritical Discourse Analysis: Language and PowerChapter 22: Text Analysis III: Analytic LogicIntroductionEthnographic Decision Models (EDM)Representing Complicated Models with Tables and IF?THEN ChartsSchema AnalysisThree Examples of Schema AnalysisAnalytic Induction/Qualitative Comparative AnalysisQualitative Comparative Analysis—QCAAnd Finally . . .Chapter 23: Univariate and Bivariate AnalysisIntroductionUnivariate Analysis: Raw DataFrequency DistributionsMeasures of Central TendencyVisualizing DataMeasures of Variation I: Range and Interquartile RangeMeasures of Variation II: Variance and the Standard DeviationThe Logic of Hypothesis TestingSo, What About the Mean of FEMILLIT?More About z-ScoresThe Univariate Chi-square TestTesting Relations: Bivariate AnalysisThe t-Test: Comparing Two MeansANOVA—Analysis of VarianceExamples of ANOVAVisualizing the Direction and Shape of CovariationsCrosstabs of Nominal VariablesCorrelation and Cause: Antecedent and Intervening VariablesChi-square for Bivariate ComparisonsTesting the Association Between Ordinal VariablesWhat to Use for Nominal and Ordinal VariablesCorrelation: The Powerhouse Statistic for CovariationSpearman’s rPearson’s rRegressionHow Regression WorksTesting the Significance of rNonlinear RelationsStatistical Significance, the Shotgun Approach, and Other IssuesChapter 24: Multivariate Analysis IntroductionElaboration: Controlling for Independent VariablesCar Wrecks and Teenage BirthsThe Multiple Regression EquationUnraveling the Teenage-birth-and-motor-vehicle-death PuzzlePath AnalysisFactor AnalysisDiscriminant Function Analysis (DFA)And Finally . . .Chapter 25: On Writing UpIntroductionGetting Your Article PublishedAppendix A: Table of Areas under a Normal Curve Appendix B: Student’s t Distribution Appendix C: Chi-square Distribution Table Appendix D: F Table for the .05 Level of Significance Appendix E: Resources for FieldworkersReferences

H. Russell Bernard is Director of the Institute for Social Science Research at Arizona State University and Professor Emeritus of Anthropology at the University of Florida. He is the author of Social Research Methods, third edition, Analyzing Qualitative Data: Systematic Approaches, second edition, and Native Ethnography.Amber Wutich is Director of the Center for Global Health and Associate Director of the Institute for Social Science Research at Arizona State University. She is the author of Social Research Methods, third edition, and The Human Story: An Introduction to Anthropology, Lazy Crazy, and Disgusting: Stigma and the Undoing of Global Health, and Analyzing Qualitative Data: Systematic Approaches, second edition.

In my courses on ethnographic methods, I have assigned multiple incarnations of H. Russell Bernard’s Research Methods in Anthropology to upper-division undergraduate and graduate students. I also use it as my own go-to guide for planning and implementing anthropological projects. The latest edition, co-authored with Amber Wutich, includes substantial additional guidance on writing proposals and drafting publications. It also contains expanded and updated material on research ethics and clarification on important qualitative methods. I look forward to assigning this updated book in the near future.

• Chapter 1: Anthropology and the Social SciencesIntroductionMethods Belong to All of UsThe Many Meanings of MethodRationalism, Empiricism, and MoralityThe Norms of ScienceThe Development of Science—From Democritus to NewtonExploration, Printing, and Modern ScienceScience, Money, and WarThe Development of Social Science—From Newton to RousseauEarly Positivism: Quételet, Saint-Simon, ComteGreat Failures in Science and Social ScienceThe Varieties of PositivismLater Positivism: The Vienna CircleInstrumental PositivismThe Reaction against PositivismAnd Finally … The Qualitative/Quantitative SplitChapter 2: The Foundations of Social ResearchIntroductionVariables: The Joy of MeasurementMeasurement and ConceptsConceptual and Operational DefinitionsConceptual DefinitionsOperational DefinitionsLevels of MeasurementReliability, Validity, Accuracy, and PrecisionDetermining ValidityUnits of AnalysisChapter 3: Preparing for ResearchIntroduction—Setting Things UpThe Ideal Research ProcessA Realistic ApproachAlternative Paradigms for Building TheoriesChoosing a Research Problem: A Guide to Research Topics, AnywayMeta-analysisChapter 4: Research DesignIntroduction: What Is Research Design?Cause and EffectThree Decisions in Research DesignThe Eight Types of Research DesignThe Components of a Research DesignThe Art of Proposal WritingHow to Develop Your Proposal with Mentors and PeersChapter 5: Experiments and Experimental ThinkingIntroductionKinds of Confounds: Threats to Internal Validity Controlling for Threats to ValidityField ExperimentsAre Field Experiments Ethical?Thought ExperimentsChapter 6: Ethics and the Conduct of AnthropologyIntroductionI: Choosing a Research ProblemII: Making Our Work Less Extractive and ExploitativeParticipatory and Action ResearchIII: Getting Informed ConsentHow to Get Your IRB Proposal ApprovedIV: Maintaining ConfidentialityChapter 7: Probability Sampling Introduction: What Are Samples and Why Do We Need Them?Sampling FramesStratified SamplingCluster Sampling and Complex Sampling DesignsMaximizing Between-group Variance: The Wichita StudyHow Big Should a Sample Be?The Normal Distribution and z-scoresThe Central Limit TheoremThe Standard Error and Confidence IntervalsCalculating Sample Size for Estimating MeansCalculating Sample Size for Estimating ProportionsChapter 8: Nonprobability Sampling Introduction: Reasons to Use a Nonprobability SampleFour Common and Two Uncommon Types of Nonprobability SamplesMinimum Sizes for Different Types of Nonprobability SamplesDeciding on a Nonprobability Sampling Method and Sample SizeAnd Finally . . .Chapter 9: Interviewing and Focus GroupsIntroduction—The Big PictureInterview ControlUnstructured InterviewingProbingLearning to InterviewPositionality and Presentation of SelfUsing a Voice RecorderUsing Visual Cues, Like Photos in InterviewsFocus GroupsResponse EffectsInformant/Respondent AccuracyChapter 10: QuestionnairesIntroductionPersonal, Face-to-face InterviewsTelephone InterviewsSelf-administered QuestionnairesWhen to Use WhatWorking with InterviewersClosed- versus Open-ended QuestionsFourteen Rules for Question Wording and FormatPretesting and Learning from MistakesTranslation and Back TranslationThe Response Rate ProblemImproving Response Rates: The Legacy of Dillman’s Total Design MethodCross-sectional and Longitudinal StudiesSome Specialized Survey MethodsAnd FinallyChapter 11: Collecting Cultural Domain DataIntroductionIt Started with the Domain of KinshipFree ListingThe True–False/Yes–No and Sentence Frame TechniquesTriad TestsFree Pile SortsRankings and Paired ComparisonsChapter 12: Collecting Social Network DataIntroduction—What Is Social Network Analysis?Anthropology and Social Network AnalysisWhole NetworksPersonal NetworksDoing Network AnalysisCollecting Whole (Sociocentric) Network DataMethods for Finding Network TiesCollecting Personal (Egocentric) Network DataReducing Respondent BurdenChapter 13: Scales and ScalingIntroductionSingle-question ScalesIndexesGuttman ScalesSome Examples of a Guttman ScaleLikert ScalesItem AnalysisTesting for Unidimensionality with Factor AnalysisThe Semantic DifferentialChapter 14: Participant ObservationIntroductionWhat Is Participant Observation?The Stages of Participant ObservationEntering the FieldFieldwork RolesThe Skills of a Participant ObserverBuilding Explicit AwarenessEthically Practicing the Darker Arts of FieldworkObjectivityStudying Your Own CultureRapid AssessmentValidity—AgainSurviving FieldworkChapter 15: Field Notes and Data ManagementIntroductionHow to Write Field NotesField NotesCoding Field NotesAnalyzing Field NotesDatabase ManagementChapter 16: Direct ObservationIntroductionCM—Continuous MonitoringCoding SchemesSpot Sampling and Time Allocation StudiesExperience Sampling (ES) and Ecological Momentary Assessment (EMA)Unobtrusive ObservationIndirect ObservationArchival ResearchChapter 17: Introduction to Data AnalysisIntroduction: Qualitative, QuantitativeData MatricesPresenting Results in Matrices and TablesPresenting Results: Causal Flow ChartsChapter 18: Analyzing Cultural Domain DataIntroductionAnalyzing Free ListsAnalyzing Pile Sort DataHow MDS WorksCluster Analysis and Pile Sort DataHow Cluster Analysis WorksA Real Research Example: Green Behavior and Electric Cars in the United StatesAnalyzing Triad DataAnalyzing Sentence FramesAnalyzing Paired ComparisonsCultural Consensus AnalysisRunning Consensus AnalysisCultural ConsonanceCultural Domains and Folk TaxonomiesChapter 19: Analyzing Network DataIntroduction: A Bit More About MatricesAnalyzing Social Network DataAnalyzing Whole (Sociocentric) Network DataAnalyzing Personal (Egocentric) Network Data“It’s Not What You Know, It’s Who You Know”Adding Network Data to the Classic RecipeAffiliation MatricesSemantic NetworksChapter 20: Analyzing Text I: Theme Coding, Grounded Theory, and Content AnalysisIntroductionOverview of Grounded TheoryContent AnalysisDoing Classical Content AnalysisIntercoder ReliabilityAI and Text AnalysisHRAF: Cross-cultural Content AnalysisDoing Cross-cultural Text-based ResearchChapter 21: Analyzing Text II: Discourse Analysis IntroductionConversation AnalysisTaking Turns in a JuryNarrative AnalysisPhenomenological Analysis of NarrativesLanguage in UseCritical Discourse Analysis: Language and PowerChapter 22: Text Analysis III: Analytic LogicIntroductionEthnographic Decision Models (EDM)Representing Complicated Models with Tables and IF?THEN ChartsSchema AnalysisThree Examples of Schema AnalysisAnalytic Induction/Qualitative Comparative AnalysisQualitative Comparative Analysis—QCAAnd Finally . . .Chapter 23: Univariate and Bivariate AnalysisIntroductionUnivariate Analysis: Raw DataFrequency DistributionsMeasures of Central TendencyVisualizing DataMeasures of Variation I: Range and Interquartile RangeMeasures of Variation II: Variance and the Standard DeviationThe Logic of Hypothesis TestingSo, What About the Mean of FEMILLIT?More About z-ScoresThe Univariate Chi-square TestTesting Relations: Bivariate AnalysisThe t-Test: Comparing Two MeansANOVA—Analysis of VarianceExamples of ANOVAVisualizing the Direction and Shape of CovariationsCrosstabs of Nominal VariablesCorrelation and Cause: Antecedent and Intervening VariablesChi-square for Bivariate ComparisonsTesting the Association Between Ordinal VariablesWhat to Use for Nominal and Ordinal VariablesCorrelation: The Powerhouse Statistic for CovariationSpearman’s rPearson’s rRegressionHow Regression WorksTesting the Significance of rNonlinear RelationsStatistical Significance, the Shotgun Approach, and Other IssuesChapter 24: Multivariate Analysis IntroductionElaboration: Controlling for Independent VariablesCar Wrecks and Teenage BirthsThe Multiple Regression EquationUnraveling the Teenage-birth-and-motor-vehicle-death PuzzlePath AnalysisFactor AnalysisDiscriminant Function Analysis (DFA)And Finally . . .Chapter 25: On Writing UpIntroductionGetting Your Article PublishedAppendix A: Table of Areas under a Normal Curve Appendix B: Student’s t Distribution Appendix C: Chi-square Distribution Table Appendix D: F Table for the .05 Level of Significance Appendix E: Resources for FieldworkersReferences