Description

Book Synopsis
Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data's contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and

Table of Contents

Preface ix

About the Companion Website xiii

1 Introduction 1

Basis of How All Quantitative Statistical Based Research 1

Data Analysis, Not Statistical Analysis 3

Quantitative Versus Qualitative Research 8

What the Book Covers and What It Does Not Cover 9

Book Structure 10

References 11

Part I Data Analysis Approaches 13

2 Statistics Terminology 15

Statistically Testing a Hypothesis 15

Statistical Significance and p-Value 19

Confidence Intervals 26

Effect Size 27

Statistical Power of a Test 31

Practical Significance Versus Statistical Significance 34

Statistical Independence 34

Degrees of Freedom 36

Measures of Central Tendency 37

Percentile and Percentile Rank 41

Central Limit Theorem 42

Law of Large Numbers 44

References 48

3 Analysis Issues and Potential Pitfalls 49

Effects of Variables 49

Outliers in the Dataset 53

Relationships Between Variables 53

A Single Contradictory Example Does Not Invalidate a Statistical Relationship 60

References 62

4 Graphically Representing Data 63

Data Distributions 63

Bell Curves 64

Skewed Curves 68

Bimodal Distributions 71

Poisson Distributions 75

Binomial Distribution 77

Histograms 79

Scatter Plots 80

Box Plots 81

Ranges of Values and Error Bars 82

References 85

5 Statistical Tests 87

Inter-Rater Reliability 87

Regression Models 92

Parametric Tests 93

Nonparametric Tests 95

One-Tailed or Two-Tailed Tests 96

Tests Must Make Sense 99

References 103

Part II Data Analysis Examples 105

6 Overview of Data Analysis Process 107

Know How to Analyze It Before Starting the Study 107

Perform an Exploratory Data Analysis 108

Perform the Statistical Analysis 109

Analyze the Results and Draw Conclusions 110

Writing Up the Study 111

References 112

7 Analysis of a Study on Reading and Lighting Levels 113

Lighting and Reading Comprehension 113

Know How the Data Will Be Analyzed Before Starting the Study 113

Perform an Exploratory Data Analysis 115

Perform an Inferential Statistical Analysis 122

Exercises 132

8 Analysis of Usability of an E-Commerce Site 135

Usability of an E-Commerce Site 135

Study Overview 135

Know How You Will Analyze the Data Before Starting the Study 136

Perform an Exploratory Data Analysis 138

Perform an Inferential Statistical Analysis 147

Follow-Up Tests 151

Performing Follow-Up Tests 153

Exercises 157

Reference 158

9 Analysis of Essay Grading 159

Analysis of Essay Grading 159

Exploratory Data Analysis 160

Inferential Statistical Data Analysis 165

Exercises 173

Reference 175

10 Specific Analysis Examples 177

Handling Outliers in the Data 177

Floor/Ceiling Effects 182

Order Effects 183

Data from Stratified Sampling 184

Missing Data 184

Noisy Data 186

Transform the Data 187

References 188

11 Other Types of Data Analysis 189

Time-Series Experiment 189

Analysis for Data Clusters 192

Low-Probability Events 193

Metadata Analysis 193

Reference 195

A Research Terminology 197

Independent, Dependent, and Controlled Variables 197

Between Subjects and Within Subjects 199

Validity and Reliability 200

Variable Types 201

Type of Data 201

Independent Measures and Repeated Measures 203

Variation in Data Collection 205

Probability—What 30% Chance Means 212

References 214

Index 215

Introduction to Quantitative Data Analysis in the

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    A Hardback by Michael J. Albers

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      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 09/06/2017
      ISBN13: 9781119290186, 978-1119290186
      ISBN10: 111929018X

      Description

      Book Synopsis
      Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data's contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and

      Table of Contents

      Preface ix

      About the Companion Website xiii

      1 Introduction 1

      Basis of How All Quantitative Statistical Based Research 1

      Data Analysis, Not Statistical Analysis 3

      Quantitative Versus Qualitative Research 8

      What the Book Covers and What It Does Not Cover 9

      Book Structure 10

      References 11

      Part I Data Analysis Approaches 13

      2 Statistics Terminology 15

      Statistically Testing a Hypothesis 15

      Statistical Significance and p-Value 19

      Confidence Intervals 26

      Effect Size 27

      Statistical Power of a Test 31

      Practical Significance Versus Statistical Significance 34

      Statistical Independence 34

      Degrees of Freedom 36

      Measures of Central Tendency 37

      Percentile and Percentile Rank 41

      Central Limit Theorem 42

      Law of Large Numbers 44

      References 48

      3 Analysis Issues and Potential Pitfalls 49

      Effects of Variables 49

      Outliers in the Dataset 53

      Relationships Between Variables 53

      A Single Contradictory Example Does Not Invalidate a Statistical Relationship 60

      References 62

      4 Graphically Representing Data 63

      Data Distributions 63

      Bell Curves 64

      Skewed Curves 68

      Bimodal Distributions 71

      Poisson Distributions 75

      Binomial Distribution 77

      Histograms 79

      Scatter Plots 80

      Box Plots 81

      Ranges of Values and Error Bars 82

      References 85

      5 Statistical Tests 87

      Inter-Rater Reliability 87

      Regression Models 92

      Parametric Tests 93

      Nonparametric Tests 95

      One-Tailed or Two-Tailed Tests 96

      Tests Must Make Sense 99

      References 103

      Part II Data Analysis Examples 105

      6 Overview of Data Analysis Process 107

      Know How to Analyze It Before Starting the Study 107

      Perform an Exploratory Data Analysis 108

      Perform the Statistical Analysis 109

      Analyze the Results and Draw Conclusions 110

      Writing Up the Study 111

      References 112

      7 Analysis of a Study on Reading and Lighting Levels 113

      Lighting and Reading Comprehension 113

      Know How the Data Will Be Analyzed Before Starting the Study 113

      Perform an Exploratory Data Analysis 115

      Perform an Inferential Statistical Analysis 122

      Exercises 132

      8 Analysis of Usability of an E-Commerce Site 135

      Usability of an E-Commerce Site 135

      Study Overview 135

      Know How You Will Analyze the Data Before Starting the Study 136

      Perform an Exploratory Data Analysis 138

      Perform an Inferential Statistical Analysis 147

      Follow-Up Tests 151

      Performing Follow-Up Tests 153

      Exercises 157

      Reference 158

      9 Analysis of Essay Grading 159

      Analysis of Essay Grading 159

      Exploratory Data Analysis 160

      Inferential Statistical Data Analysis 165

      Exercises 173

      Reference 175

      10 Specific Analysis Examples 177

      Handling Outliers in the Data 177

      Floor/Ceiling Effects 182

      Order Effects 183

      Data from Stratified Sampling 184

      Missing Data 184

      Noisy Data 186

      Transform the Data 187

      References 188

      11 Other Types of Data Analysis 189

      Time-Series Experiment 189

      Analysis for Data Clusters 192

      Low-Probability Events 193

      Metadata Analysis 193

      Reference 195

      A Research Terminology 197

      Independent, Dependent, and Controlled Variables 197

      Between Subjects and Within Subjects 199

      Validity and Reliability 200

      Variable Types 201

      Type of Data 201

      Independent Measures and Repeated Measures 203

      Variation in Data Collection 205

      Probability—What 30% Chance Means 212

      References 214

      Index 215

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