A Guide to Teaching Statistics: Innovations and Best Practices

Series Editors’ Preface xiii

Preface xvii

Part I Course Preparation 1

1 Teaching Statistics: A Beginning 3

So Why Teach Statistics? 5

Historical Pedagogical Controversies 7

Who should teach statistics? 7

Statistics labs and related technology 8

Content of statistics courses 10

Statistics in Relation to the Discipline 11

Sequence of the Class and Topics 12

Introducing Research Methods within the Context of Statistics 16

Student Populations 17

Mathematical ability 17

Cognitive ability and learning styles 19

Self-efficacy and motivation 20

Gender 22

Helping Your Students Survive Statistics 23

Conclusion 25

2 Nuts and Bolts of Teaching Statistics 27

Syllabus Construction 28

Textbook Selection 30

Conceptual orientation 31

Level of difficulty 33

Chapter topics and organization 34

Core formulas and vocabulary 35

Type of data sets/quality of the exercises 36

Traditional Versus Electronic Textbooks 37

Supplemental Materials 38

Study guides 39

Companion Web sites 39

Computer tutorials 40

Electronic Discussion Boards 42

Multimedia Tools 44

Presentation technology 45

Interactive applications: Java applets, Flash, Shockwave, and HTML 46

Multimedia simulation programs 48

Conclusion 49

Part II Theoretical and Pedagogical Concerns 51

3 Educational Reform in Statistics 53

Educational Reform 54

Statistically Educated Students 56

Statistical Literacy 59

Knowledge elements 60

Dispositional elements 62

Statistical Thinking 63

Statistical Reasoning 66

Misconceptions Impacting the Development of Literacy, Thinking, and Reasoning 70

Final Thoughts on Statistical Literacy, Thinking, and Reasoning 72

Assessment 73

What is the role of assessment? 73

What is the role of authentic assessment? 74

Assessment and learning outcomes or goals 75

Conclusion 77

4 In the Classroom 79

Conceptual Learning, Active Learning, and Real Data 80

Conceptual learning versus rote memorization 80

Active learning 82

Real data 83

Instructional Techniques 84

Lecture 85

The use of questions 86

Practice problems and examples 87

Journal assignments 88

Activities and demonstrations 89

Writing assignments 90

Concept maps 93

Cooperative learning 94

Projects 95

Assessment 97

Principles of effective assessment 97

Mastery learning 98

Confronting Fear and Anxiety 99

Conclusion 101

Part III Teaching Specific Statistical Concepts 103

5 Descriptive Statistics and Bivariate Distributions 105

Graphing Data 106

The use of graphs in science 107

Elements of good design 108

Human graphical perception 109

Available graphing methods 110

Software design 111

Normal Distribution 112

Measures of Central Tendency 114

Measures of Variability 117

Correlation 119

Simple Linear Regression 122

Computer Applications 125

Conclusion 127

6 Teaching Hypothesis Testing 129

Samples, Sampling Distributions, and the Central Limit Theorem 131

Confidence Intervals 133

Introduction to Null Hypothesis Testing 135

Additional Introduction to Hypothesis Testing Concepts 138

Power 138

Effect sizes 140

Type I and Type II errors 141

Analysis of Variance 142

Introduction to ANOVA 142

Violating ANOVA assumptions 143

Factorial ANOVA 144

General linear model 145

The Debate Surrounding Null Hypothesis Significance Testing 146

Nonparametric Statistics 146

Computer Applications 149

Conclusion 151

Part IV Advanced Topics and Approaches 153

7 Data Analysis in Statistical Education 155

Teaching with Statistical Software Tools 156

Data Analysis Packages 158

SPSS 158

Microsoft Excel 160

Other commercial data analysis programs 162

Comparing data analysis programs 163

Data Analysis Software Textbooks 165

Using Data Sets in the Classroom 166

Artificial data sets for the classroom 167

Reality-based data sets 168

Finding appropriate reality-based data sets 169

Drawbacks to using real data sets 174

Conclusion 176

8 Endings and Beginnings 179

Multivariate Statistics 180

Multiple regression 182

Logistic regression 184

Additional multivariate techniques 185

Special Topics 186

Ethics 187

Diversity 190

Online Statistical Education 193

Finishing up Any Statistics Course 195

Final Thoughts 198

References 201

Index 248