Workshop Statistics: Discovery with Data, 3rd Edition
June 2008, ©2008
To the Student.
Organization of Workshop Statistics.
List of Activities by Application.
List of Activities Using Student-Generated Data.
UNIT 1. Collecting Data and Drawing Conclusions.
TOPIC 1 Data and Variables.
TOPIC 2 Data and Distributions.
TOPIC 3 Drawing Conclusions from Studies.
TOPIC 4 Random Sampling.
TOPIC 5 Designing Experiments.
UNIT 2. Summarizing Data.
TOPIC 6 Two-Way Tables.
TOPIC 7 Displaying and Describing Distributions.
TOPIC 8 Measures of Center.
TOPIC 9 Measures of Spread.
TOPIC 10 More Summary Measures and Graphs.
UNIT 3. Randomness in Data.
TOPIC 11 Probability.
TOPIC 12 Normal Distributions.
TOPIC 13 Sampling Distributions: Proportions.
TOPIC 14 Sampling Distributions: Means.
TOPIC 15 Central Limit Theorem.
UNIT 4. Inference from Data: Principles.
TOPIC 16 Confidence Intervals: Proportions.
TOPIC 17 Tests of Significance: Proportions.
TOPIC 18 More Inference Considerations.
TOPIC 19 Confidence Intervals: Means.
TOPIC 20 Tests of Significance: Means.
UNIT 5. Inference from Data: Comparisons.
TOPIC 21 Comparing Two Proportions.
TOPIC 22 Comparing Two Means.
TOPIC 23 Analyzing Paired Data.
UNIT 6. Inferences with Categorical Data.
TOPIC 24 Goodness-of-Fit Tests.
TOPIC 25 Inference for Two-Way Tables.
UNIT 7. Relationships in Data.
TOPIC 26 Graphical Displays of Association.
TOPIC 27 Correlation Coefficient.
TOPIC 28 Least Squares Regression.
TOPIC 29 Inference for Correlation and Regression.
TABLE I Random Digits.
TABLE II Standard Normal Probabilities.
TABLE III t-Distribution Critical Values.
TABLE IV Chi-Square Distribution Critical Values.
APPENDIX A Student Glossary.
APPENDIX B Sources for Studies and Datasets.
APPENDIX C List of Data Files and Applets.
Allan Rossman received his PhD in statistics from Carnegie Mellon University. Before he came to Cal Poly, he taught for twelve years at Dickinson College in Pennsylvania, where he served a term as department chair. He is president of the International Association for Statistics Education from 2007–2009 and was the Program Chair for the 2007 Joint Statistical Meetings. He has served as chair of the ASA's Section on Statistical Education and of the ASA/MAA Joint Committee on Undergraduate Statistics. He was selected as Fellow of the American Statistical Association in 2001. Allan served as project director for the Mathematical Association of America's NSF-funded STATS (Statistical Thinking with Active Teaching Strategies) project, which conducted workshops for mathematicians who teach statistics.
Beth Chance received her PhD in operations research, with an emphasis in statistics and a minor in education from Cornell University. She taught at University of the Pacific before moving to Cal Poly. She has served on the Test Development Committee for Advanced Placement Statistics and as secretary/treasurer of the ASA Section on Statistical Education. She was the inaugural recipient of the American Statistical Association's Waller Education Award for Excellence and Innovation in Teaching Introductory Statistics in 2002 and received the 2003 Mu Sigma Rho Statistical Education Award. She was selected as a Fellow of the ASA in 2005. Beth's professional interests include development of curricular materials for introductory statistics and research into how students learn statistics, particularly on the role of assessment and technology. She and her collaborators have published in the Journal of Statistics Education and the Statistics Education Research Journal (SERJ), and she has collaborated on several chapters and books aimed at enhancing teacher preparation to teach statistics. She currently serves as the assistant editor for SERJ.
Many new activities that present students with authentic studies that address specific research questions, helping them to recognize the power of statistics to answer questions of genuine interest in everyday life
New and updated data sets from real studies, such as fat content in ice cream brands, textbook prices, etc.
Watch Out points added to all topics to help students develop useful statistical habits
Self-Check Examples with detailed solutions added to all topics so students can check their work and assess their understanding
Wrap-Up sections have been greatly expanded to provide more information about the material covered in the topic
Additional coverage has been added on probability, random variables, the binomial distribution, and Analysis of Variance through the Web-based Student Resource Center
An attractive new design adds visual appeal and clarifies the features as well as facilitates navigation between features and topics
Activities utilize the principles of student engagement and active learning and place stronger emphasis on developing students' conceptual understanding of key statistical ideas
Focus is on real, genuine data that students generate themselves to teach the real-world relevance of statistics
Nearly half the activities require the use of a software package or graphing calculator, but this version of the text refers to technology generically and does not provide instructions for particular software
Teaches and requires group work, student writing and communication, and problem identification and solving
Models the philosophy and conforms to the research conclusions of two important sets of studies and recommendations: Garfield's "How Students Learn Statistics" and the "GAISE Guidelines"