A Guide to Teaching Statistics Innovations and Best Practices

by Hulsizer, Michael R.; Woolf, Linda M.

• ISBN13: 9781405155748
• ISBN10: 1405155744
• Edition: 1st
• Format: Paperback
• Copyright: 2008-10-06
• Publisher: Wiley-Blackwell

Summary

Teaching Statistics: Innovations and Best Practices addresses the critical aspects of teaching statistics to undergraduate students, acting as an invaluable tool for both novice and seasoned teachers of statistics.

Author Biography

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.

Table of Contents

Series EditorsÆ Preface

Preface

Course Preparation

Teaching Statistics: A Beginning

So Why Teach Statistics?

Historical Pedagogical Controversies

Who should teach statistics?

Statistics labs and related technology

Content of statistics courses

Statistics in Relation to the Discipline

Sequence of the Class and Topics

Introducing Research Methods within the Context of Statistics

Student Populations

Mathematical ability

Cognitive ability and learning styles

Self-efficacy and motivation

Gender

Helping Your Students Survive Statistics

Conclusion

Nuts and Bolts of Teaching Statistics

Syllabus Construction

Textbook Selection

Conceptual orientation

Level of difficulty

Chapter topics and organization

Core formulas and vocabulary

Type of data sets/quality of the exercises

Traditional Versus Electronic Textbooks

Supplemental Materials

Study guides

Companion Web sites

Computer tutorials

Electronic Discussion Boards

Multimedia Tools

Presentation technology

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

Multimedia simulation programs

Conclusion

Theoretical and Pedagogical Concerns

Educational Reform in Statistics

Educational Reform

Statistically Educated Students

Statistical Literacy

Knowledge elements

Dispositional elements

Statistical Thinking

Statistical Reasoning

Misconceptions Impacting the Development of Literacy, Thinking, and Reasoning

Final Thoughts on Statistical Literacy, Thinking, and Reasoning

Assessment

What is the role of assessment?

What is the role of authentic assessment?

Assessment and learning outcomes or goals

Conclusion

In the Classroom

Conceptual Learning, Active Learning, and Real Data

Conceptual learning versus rote memorization

Active learning

Real data

Instructional Techniques

Lecture

The use of questions

Practice problems and examples

Journal assignments

Activities and demonstrations

Writing assignments

Concept maps

Cooperative learning

Projects

Assessment

Principles of effective assessment

Mastery learning

Confronting Fear and Anxiety

Conclusion

Teaching Specific Statistical Concepts

Descriptive Statistics and Bivariate Distributions

Graphing Data

The use of graphs in science

Elements of good design

Human graphical perception

Available graphing methods

Software design

Normal Distribution

Measures of Central Tendency

Measures of Variability

Correlation

Simple Linear Regression

Computer Applications

Conclusion

Teaching Hypothesis Testing

Samples, Sampling Distributions, and the Central Limit Theorem

Confidence Intervals

Introduction to Null Hypothesis Testing

Additional Introduction to Hypothesis Testing Concepts

Power

Effect sizes

Type I and Type II errors

Analysis of Variance

Introduction to ANOVA

Violating ANOVA assumptions

Factorial ANOVA

General linear model

The Debate Surrounding Null Hypothesis Significance Testing

Nonparametric Statistics

Computer Applications

Conclusion

Advanced Topics and Approaches

Data Analysis in Statistical Education

Teaching with Statistical Software Tools

Data Analysis Packages

SPSS

Microsoft Excel

Other commercial data analysis programs

Comparing data analysis programs

Data Analysis Software Textbooks

Using Data Sets in the Classroom

Artificial data sets for the classroom

Reality-based data sets

Finding appropriate reality-based data sets

Drawbacks to using real data sets

Conclusion

Endings and Beginnings

Multivariate Statistics

Multiple regression

Logistic regression

Additional multivariate techniques

Special Topics

Ethics

Diversity

Online Statistical Education

Finishing up Any Statistics Course

Final Thoughts

References

Index

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