Kieth A. Carlson and Jennifer R. Winquist
Evaluating an active learning approach to teaching introductory statistics: A classroom workbook approach

The study evaluates a semester-long workbook curriculum approach to teaching a college level introductory statistics course. The workbook curriculum required students to read content before and during class and then work in groups to complete problems and answer conceptual questions pertaining to the material they read. Instructors spent class time answering students' questions. The 59 students who experienced the workbook curriculum completed the Survey of Attitudes Toward Statistics (SATS) on the first and last day of the course. These students' post course ratings on the subscales of cognitive competence, affect and difficulty were all significantly higher than their pre course ratings. Additionally, the 59 students' post course ratings for these 3 subscales were also significantly higher than those provided by a comparison group of statistics students (sample size 235). The results indicated that the students experiencing the workbook curriculum (1) had more confidence in their ability to perform and understand statistics, (2) liked statistics more, and (3) thought statistics was more difficult than the comparison group. Additionally, these students' attitude scores were positively correlated with both GPA and performance on a comprehensive final exam. We discuss the various methodological problems faced by classroom researchers and suggest that, in some cases, assessing students' attitudes can be an effective solution to these methodological problems. We conclude that the workbook approach holds promise for teaching introductory statistics courses.

Key Words: Active learning; Student attitudes; Curriculum assessment; Course evaluation; Instructor immediacy.

Stephen E. Hill and Shane J. Schvaneveldt
Using Statistical Process Control Charts to Identify the Steroids Era in Major League Baseball: An Educational Exercise

This article presents an educational exercise in which statistical process control charts are constructed and used to identify the Steroids Era in American professional baseball. During this period (roughly 1993 until the present), numerous baseball players were alleged or proven to have used banned, performance-enhancing drugs. Also observed during this period was an increase in offensive performance. In this exercise, students are given the opportunity to construct trial control limits from historical data, consider the presence of random and assignable cause variation, and analyze offensive performance for the 1993 to 2008 baseball seasons. From this analysis, students can consider the potential impact of performance-enhancing drugs on offensive performance in Major League Baseball.

Key Words: Statistical Quality Control; Control Charts; Sports; Innovative Education.

John Lawson, Pankaj Aggarwal, Thomas Leininger, and Kenneth Fairchild
Characterizing Variability in Smestad and Gratzel’s Nanocrystalline Solar Cells: A Collaborative Learning Experience in Experimental Design

This article describes a collaborative learning experience in experimental design that closely approximates what practicing statisticians and researchers in applied science experience during consulting. Statistics majors worked with a teaching assistant from the chemistry department to conduct a series of experiments characterizing the variation in measured voltage output of Smestad and Gratzel’s nanocrystaline titanium dioxide (TiO2) solar cells. These solar cells can be constructed easily in a laboratory, and they are reported to produce an open circuit voltage in direct sunlight of 0.3 to 0.5V. Statistics students planned a series of experiments as part of an experimental design class, and the chemistry TA performed the experiments in the lab where the statistics students could observe. The students wrote a description of what they did and the results. From the students’ comments about what they learned from this experience, it appears that this type of exercise could be very beneficial in training future consulting statisticians and scientists or technologists who will use experimentation in their work.

Key Words: Variance Component, Staggered Nested Design, Complex Aliasing, Plackett-Burman Design

Nathan Tintle, Jill VanderStoep, Vicki-Lynn Holmes, Brooke Quisenberry, and Todd Swanson
Development and assessment of a preliminary randomization-based introductory statistics curriculum

The algebra-based introductory statistics course is the most popular undergraduate course in statistics. While there is a general consensus for the content of the curriculum, the recent Guidelines for Assessment and Instruction in Statistics Education (GAISE) have challenged the pedagogy of this course. Additionally, some arguments have been made that the curriculum should focus on a randomization approach to statistical inference instead of using asymptotic tests. We developed a preliminary version of a randomization based curriculum which we then implemented with 240 students in eight sections of introductory statistics in fall 2009. The Comprehensive Assessment of Outcomes in Statistics (CAOS) assessment test was administered to these students and showed that students learned significantly more about statistical inference using the new curriculum, with comparable learning on most other questions. The assessment results demonstrate that refining content, improving pedagogy and rethinking the consensus curriculum can significantly improve student learning. We will continue to refine both content and pedagogy resulting in improved student learning gains on CAOS items and other assessment measures.

Key Words:CAOS; Inference; Permutation test.

Pedro M. Valero-Mora and Rubén D. Ledesma
Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the analysis "by hand," using techniques such as pointing at, selecting and changing the colors of the points/observations. Our experience demonstrates that this approach is very useful when teaching an intermediate/advanced course on multivariate data analysis to students of Psychology, who tend to have low to moderate proficiency in Mathematics.

Key Words: Interactive graphics; Multivariate data; Parallel boxplots; Principal components; Cluster analysis.

Thomas Walsh, Jr.
Implementing Project Based Survey Research Skills to Grade Six ELP Students with The Survey Toolkit and TinkerPlots®

Survey Toolkit Collecting Information, Analyzing Data and Writing Reports (Walsh, 2009a) is discussed as a survey research curriculum used by the author's sixth grade students. The report describes the implementation of The Survey Toolkit curriculum and TinkerPlots® software to provide instruction to students learning a project based research methodology using surveys for the last six years. The article presents classroom instructional strategies to more effectively deliver the curriculum, along with examples of student work. Research supporting the teaching of statistics across the curriculum, implementation considerations, and an introduction of the development and organization of The Survey Toolkit is provided. Use of the curriculum with students focusing on findings from their selected sample, cognizant of inferential research methods (e.g., hypothesis testing) and not being able to generalize findings to a population is discussed. A piloted formal assessment and rubric evaluation of completed survey projects provides evidence of the learning skills and competencies students acquire using the curriculum model. The need for further research to evaluate the effectiveness of the curriculum materials, student learning, and staff development is discussed.

Key Words: Survey research methodology; student project samples; data and statistics teaching curriculum; effective teaching strategies; student learning and evaluation, staff development, and research recommendations.

Jason Wilson, Joshua Lawman, Rachael Murphy, and Marissa Nelson
A Comprehensive Probability Project for the Upper Division One-Semester Probability Course Using Yahtzee

This article describes a probability project used in an upper division, one-semester probability course with third-semester calculus and linear algebra prerequisites. The student learning outcome focused on developing the skills necessary for approaching project-sized math/stat application problems. These skills include appropriately defining terms, making necessary simplifying assumptions, budgeting time, determining when to search literature, and checking theoretical calculations with simulation. It was assumed students would learn the technical material in the process. The result exceeded expectations. This article is written to summarize the project, provide a complete solution (including R code with simulations and theoretical solutions), and describe the methods which facilitated the positive outcome, with the hope that it might be adapted by others.

Key Words: Markov chain; Probability; Project; Yahtzee

Jimmie Leppink, Nick J. Broers, Tjaart Imbos, Cees P. M. van der Vleuten, and Martijn P. F. Berger
Exploring task- and student-related factors in the method of propositional manipulation (MPM)

The method of propositional manipulation (MPM) aims to help students develop conceptual understanding of statistics by guiding them into self-explaining propositions. To explore task- and student-related factors influencing students' ability to learn from MPM, twenty undergraduate students performed six learning tasks while thinking aloud. The results indicate that whether students learn from MPM depends on their statistics proficiency level, the subject matter, the number of propositions in the learning task, and the instructions. MPM learning tasks should be tailored to the students' level of expertise and students should be instructed more than once to integrate all propositions in the learning task into their arguments.

Key Words: Statistics education; Method of propositional manipulation (MPM); Conceptual understanding; Guided self-explanation; Cognitive load.

M. Leigh Lunsford and Phillip Poplin
From Research to Practice: Basic Mathematics Skills and Success in Introductory Statistics

Based on previous research of Johnson and Kuennen (2006), we conducted a study to determine factors that would possibly predict student success in an introductory statistics course. Our results were similar to Johnson and Kuennen in that we found students' basic mathematical skills, as measured on a test created by Johnson and Kuennen, were a significant predictor of student success in the course. We also found a significant professor effect. These results have prompted us to evaluate and modify the teaching of our introductory statistics course.

Key Words: Assessment; Basic mathematical skills; Introductory statistics.

Audbjorg Bjornsdottir and Joan Garfield
Teaching Bits: Statistics Education Articles from 2010 and 2011

We located 25 articles that have been published from October 2010 through January 2011 that pertained to statistics education. In this column, we highlight a few of these articles that represent a variety of different journals that include statistics education in their focus. We also provide information about the journal and a link to their website so that abstracts of additional articles may be accessed and viewed.

Michelle Everson and Ellen Gundlach
Teaching Bits: What's new with CAUSEWeb and MERLOT?

This month, we highlight some upcoming conferences--the United States Conference on Teaching Statistics (USCOTS) and the Emerging Technologies for Online Learning Conference--and we also share many of the new Teaching and Learning and Activity webinars featured on CAUSEweb. With the approach of spring comes many new CAUSEweb and MERLOT resources!

Christopher E. Barat, Courtney Wright, and Betty Chou
Examining Potential Predictors for Completion of the Gardasil Vaccine Sequence Based on Data Gathered at Clinics of Johns Hopkins Medical Institutions

This paper presents categorical data that were gathered at two urban clinics and two suburban clinics of Johns Hopkins in an effort to identify characteristics of young female patients who successfully complete the three-injection sequence of the Gardasil quadrivalent human papillomavirus vaccine (HPV4). Available categorical correlates included patient age group, patient race, clinic location type, type of insurance provider, and clinic practice type. The data may be used to illustrate graphical display techniques and inference procedures for categorical data, as well as illuminate ways in which relationships between categorical variables may be hidden or behave differently than expected in the presence of confounding variables. The methods used to gather the data may also serve to illustrate the limitations of drawing conclusions from observational studies.

Key Words: Categorical data; Chi-square test of homogeneity; Confounding variables; Inference for proportions; Logistic regression; Odds ratio.

Concetta A. DePaolo and David F. Robinson
Café Data

In this paper we present time series data collected from a café run by business students at a Midwestern public university. The data were collected over a ten-week period during the spring semester of 2010. These data can be used in introductory courses to illustrate basic concepts of time series and forecasting, including trend, seasonality, and the use of time series decomposition. Since the data relate to a student-run enterprise, we believe that statistics students, especially those in business disciplines, will find the application interesting and engaging. In addition to exercises in which students can perform statistical analyses, we also provide several examples in which the data and results are related to the business context, thereby showing the relevance and importance of data-driven business decisions.

Key Words: Time series; Forecasting; Trend; Decomposition; Regression; Correlation.