1. COMPARISONS AND CONCLUSIONS. Summarizing Categorical Data. Analyzing Categorical Data. Confounding. Designing Experiments. Assessing Statistical Significance. Probability and Counting Methods. Fisher's Exact Test. 2. COMPARISONS WITH QUANTITATIVE VARIABLES. Summarizing Quantitative Data. Statistical Significance. 3. SAMPLING FROM POPULATIONS. Selecting Samples from Populations I. Sampling from a Process. Exact Binomial Inference. Sampling from a Population II. 4. MODELS AND SAMPLING DISTRIBUTIONS. Models of Quantitative Data. Applying the Normal Probability Model. Distributions of Sample Counts and Proportions. Distributions of Sample Means. Bootstrapping. 5. COMPARING TWO POPULATIONS. Comparing Two Samples on a Categorical Response. Randomized Experiments Revisited. Comparing Two Samples on a Quantitative Response. 6. COMPARING SEVERAL POPULATIONS, EXPLORING RELATIONSHIPS. Two Categorical Variables. Comparing Several Population Means. Relationships Between Quantitative Variables. Inference for Regression.
Allan Rossman has been an Associate Professor in the Department of Statistics at California Polytechnic State University in San Luis Obispo since 2001. Prior to moving to the West Coast, Dr. Rossman taught at Dickinson College from 1989 to 2001 and received his undergraduate and graduate degrees respectively at Geneva College and Carnegie Mellon University. Dr. Rossman is the originator of the WORKSHOP STATISTICS series of course books that lead students to explore and discover fundamental concepts and methods of statistics. He directed one of the MAA's NSF-funded STATS projects that conducted workshops for mathematicians who teach statistics. Dr. Rossman has chaired the ASA/MAA Joint Committee on Undergraduate Statistics and the ASA's Section on Statistical Education. He was co-editor of STATS magazine and serves on the International Program Committee for the International Conference on Teaching Statistics. Elected as a Fellow of ASA in 2001, Dr. Rossman has given presentations and conducted workshops on the teaching of statistics around the world. Beth Chance has been an Associate Professor in the Department of Statistics at California Polytechnic State University in San Luis Obispo since 1999. She earned a B.S. in Applied Mathematics from Harvey Mudd College and an M.S. and Ph.D. in Operations Research from Cornell University; she previously taught at the University of the Pacific. She serves on the AP Statistics Test Development Committee, on the ASA/MAA Joint Committee on Undergraduate Statistics, and as Secretary/Treasurer of the ASA's Section on Statistical Education. She is co-author of the WORKSHOP STATISTICS series of texts and was co-editor of STATS magazine. Dr. Chance's research in statistics education has focused on effective use of technology and on authentic assessments of students' development of statistical thinking. She is co-PI on the NSF-funded ARTIST (Assessment Resource Tools for Improving Statistical Thinking) project. Dr. Chance has given presentations and conducted workshops on statistics education around the world, and she has been honored as the inaugural recipient of the ASA's Waller Education Award in 2002 and with the Mu Sigma Rho Statistical Education Award in 2003.
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