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.
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.
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
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.
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.
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.
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
From Research to Practice
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.
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.
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.
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!
Data Sets and Stories
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
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.