Principal Investigators: Allan
Rossman, Beth Chance
Department of Statistics,
Cal
Poly  San Luis Obispo
funded by NSF/DUE/CCLI #9950746, 0321973
Project Overview
This project aims to develop curricular materials for a course that introduces students at the postcalculus level to statistical concepts, applications, and theory. This course provides a more balanced introduction to the discipline of statistics than the standard sequence in probability and mathematical statistics. The materials incorporate many features of successful statistics education projects that target less mathematically prepared students. The student audiences targeted by this project are particularly important because they have been overlooked by previous curricular reform projects. Most importantly, the proposed audience includes prospective teachers of statistics, introducing them to content and pedagogy that prepare them for implementing NCTM Standards with regard to statistics and probability and for teaching the Advanced Placement course in Statistics.
Information
and supplementary resources for forthcoming preliminary edition of
Investigating Statistical Concepts, Applications, and Methods
Contact Duxbury Press for more information

Course Principles
Some of the principles that have guided the development of these materials
are:
Motivate with real studies and genuine data. Emphasize connections among study design, inference technique, and scope of conclusion. Conduct simulations often. Use variety of computation tools. Investigate mathematical underpinnings. Introduce probability just in time. Foster active explorations. Experience the entire statistical process over and over again.

Content Outline
oChapter
1: Comparisons and Conclusions descriptive analyses of 2x2 tables
(segmented bar graphs, conditional proportions, relative risk, odds ratio),
types of variables, observational studies vs. controlled experiments, confounding
variables, causation, randomization, Simpsons paradox, statistical significance,
hypergeometric distribution, Fisher's Exact Test
oChapter
2: Comparisons with Quantiative Variables  graphical and numerical
descripitive analyses of quantitative variables (dotplots, boxplots, histograms,
stemplots), measures of center and variability, empirical rule, zscore,
resistance, simulating a randomization test, effect of sample size
oChapter 3: Sampling parameter vs. statistic, sampling bias, precision, simple random sampling, probability samples, binomial distribution, binomial tests and confidence intervals, effect of sample size, type I and II error, power, sign test oChapter 4: Models and Sampling Distributions  models, normal distribution, normal probability plots, normal approximation to binomial, large sample z procedures, exploration of confidence, Central Limit Theorem, tprocedures, paired ttests, prediction intervals, bootstrapping oChapter 5: Comparing Two Populations  comparing proportions (zprocedures, oddsratios, randomized experiments), comparing means (tprocedures, randomization distribution), bootstrapping oChapter 6: Comparing Several Populations, Exploring Relationships  Chisquare tests of homogeneity and association, Analysis of Variance, scatterplots, correlation coefficient, leastsquares regression, inference for regression 