Guide to Teaching Statistics is an invaluable tool for both novice and seasoned teachers of statistics. The book provides pedagogical methods and activities for teaching a range of topics, from simple statistics such as mean, median, and mode to much more complex analyses such as multivariate analyses of variance. It addresses the tools used for teaching statistics from the traditional pencil and calculator to computer programs such as SPSS. It also features topics unique to the teaching of statistics, such as working with math phobic and special needs students. A Guide to Teaching…mehr
Guide to Teaching Statistics is an invaluable tool for both novice and seasoned teachers of statistics. The book provides pedagogical methods and activities for teaching a range of topics, from simple statistics such as mean, median, and mode to much more complex analyses such as multivariate analyses of variance. It addresses the tools used for teaching statistics from the traditional pencil and calculator to computer programs such as SPSS. It also features topics unique to the teaching of statistics, such as working with math phobic and special needs students.A Guide to Teaching Statistics: Innovations and Best Practices, by Michael R. Hulsizer and Linda M. Woolf, is an invaluable guide for both novice and seasoned teachers of statistics. Based on an extensive review of the research in fields such as education, health sciences, mathematics, statistics, psychology, and the social sciences, the book covers a range of statistics education and assessment topics. The book also includes novel classroom exercises, pedagogical tools, and computer applications designed to enhance active learning. Topics include descriptive, inferential, and multivariate statistics as well as the importance of using real data in the classroom, the role of ethics and diversity in statistics, and the effectiveness of online statistical education. The authors also provide extensive coverage of the research concerning statistical literacy, thinking, and reasoning.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Michael R. Hulsizer is Associate Professor of Experimental Psychology at Webster University in St. Louis, Missouri, where he was honored with the prestigious William T. Kemper Award for Excellence in Teaching (2002). He has attended numerous National Institute on the Teaching of Psychology conferences and has won awards for posters presented at the conference. Michael has coauthored several teaching resources available at the Office of Teaching Resources in Psychology - Online. In addition, he recently contributed a chapter with Linda on incorporating diversity into research methods for Best Practices for Teaching Statistics and Research Methods in the Behavioral Sciences. Michael has also authored articles on mass violence, hate groups, and interpersonal aggression. Linda M. Woolf is Professor of Experimental and Peace Psychology at Webster University. Linda is the recipient of several teaching awards including the 1988 Early Career Award from the Society for the Teaching of Psychology (Division 2, APA), Emerson Electric Excellence in Teaching Award (1990, 2000), and William T. Kemper Award for Excellence in Teaching (2000). She has authored numerous curriculum resources, book chapters, and journal articles concerning international psychology, peace psychology, mass violence, human rights, and research methods. Linda is Past-President of the Society for the Study of Peace, Conflict, and Violence (Division 48, APA) and former Secretary and Newsletter Editor for the Society for the Teaching of Psychology.
Inhaltsangabe
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
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
Rezensionen
"In the book the reader will not find a collection of statisticaltables or formulae but a rich collection of references on teachingof statistics in several fields, e.g. psychology, social sciences,health sciences, education." (Zentralblatt MATH, 2010)
"It's a heartfelt pleasure to recommend this book. It'spacked with useful information on texts, assignments,demonstrations, means of assessment, and technologies relevant tothe teaching of statistics, and it's also the moststimulating and thoughtful scholarly treatment of the teaching ofstatistics I have ever seen." -Neil Lutsky, Carleton College
"In Teaching Statistics, Hulsizer and Woolf provide awell organized and clear presentation of the important issues thatface teachers at all levels, from basic to advanced. The coverageis complete and the material presented is based on the results ofempirical studies as well as the authors own experiences.Especially for new teachers, the book will be an important tool tohelp them find their teacher's voice." -Neil Salkind, Professor Emeritus, University ofKansas
"Michael Hulsizer and Linda Woolf have put together a clearlywritten guide to teaching statistics that is based on acomprehensive review of literature in statistics education.Although the book is oriented toward teaching statistics inpsychology departments, anyone who teaches statistics will benefitfrom this book, especially those new to the endeavor. The book isfull of well-researched advice and guidance on teaching statisticsthat reflects current recommendations from the statistics educationreform movement, as well as sound principles for instructiongleaned from the learning and cognition research literature. Itwill have a prominent place among my teaching resources." -Bob delMas, University of Minnesota…mehr
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