In this paper we present an application of statistics using real stock market data. Most,
if not all, students have some familiarity with the stock market (or at least they have heard
about it) and therefore can understand the problem easily. It is the real data analysis that
students find interesting. Here we explore the building of efficient portfolios through optimization
using examples of two and three stocks, and how covariance and correlation can help the investor to
diversify his or her risk. We discuss why diversification works, but also the problems that arise
in portfolio management. Stock market data can be incorporated at any level of statistics, from
lower division, to upper division, to graduate courses of Mathematics and Statistics. From our
experience, students find this topic very interesting and often they want to enroll in other
courses related to this area.
Key Words: Efficient frontier; Covariance; Portfolio risk and return; Stock market.
Globalization is bringing about a radical "rethink" regarding the delivery of graduate management
education. Today, manystudents entering a residential MBA program do not possess an undergraduate
degree in business. As a result, many business schools are increasingly turning to the Internet to
provide "customized" instructional content to ensure that students can remain competitive throughout
the program. The purpose of this paper is threefold: 1) to estimate student performance in a
residential MBA program; 2) to outline a process for identifying specific learning support resources
based on student backgrounds and capabilities; and 3) to illustrate the screening process in providing
business statistics support content to students requiring additional preparation. The results show
that neural net based classification techniques can effectively identify students
for the purpose of providing additional learning resources. Business statistics is one area in which this
screening process has been used to deliver specialized content to students with
a variety of backgrounds enrolled in a MBA residential program.
Key Words: Residential MBA programs; Learning support systems; Intelligent agents;
Neural nets; Business statistics.
This paper presents an overview of modalities that can be used to make learning statistics fun.
Representative examples or points of departure in the literature are provided for no less than 20
modalities. Empirical evidence of effectiveness specific to statistics education is starting to
emerge for some of these modalities - namely, humor, song, and cartoons. To reinforce their
effectiveness as an intentional teaching tool, the authors offer practical implementation tips.
Key Words: Anxiety; Cartoons; Humor; Fun; Motivation; Song; Statistics Education.
This note presents a spreadsheet tool that allows teachers the opportunity to guide students towards
answering on their own questions related to the multiple regression F-test, the t-tests, and
multicollinearity. The note demonstrates approaches for using the spreadsheet that might be
appropriate for three different levels of statistics classes, so teachers can select the context
that is most appropriate for their particular needs. The spreadsheet tool is linked to this article,
and materials are provided in the appendices for teachers to use as handouts, homework questions,
and answer keys.
Key Words: Joint influence; Multicollinearity; F-test confidence region;
T-test confidence interval.
The present study addresses the efficacy of using service-learning methods to meet the GAISE
in a second business statistics course and further explores potential advantages of assigning a
service-learning (SL) project as compared to the traditional statistics project assignment.
Second semester business students were given the choice of participating in a SL project or
doing a traditional project assignment.
When the projects were completed, students reflected on their experiences via survey. Both
groups responded equally (agree or strongly agree) to the Likert scale questions: 96.15% reinforced
learning objectives, 98.08% applied to real world, 84.62% positive experience. Responses to the open
ended questions revealed that more students in the SL group (p = 0.019) wrote about the benefits of
dealing with real world data, more SL students felt their work benefited others (65% felt their
statistical expertise was valuable) and more (p=0.005) SL students felt that the experience will
help them in future classes. These results suggest that while both groups were able to effectively
support the GAISE guidelines, participation in the SL option offered an enhanced learning experience
that included elements of social responsibility and personal growth. The experience was perceived
more enjoyable and relevant to the real world adding elements of student empowerment while
assisting a local agency in need of statistical expertise suggesting one can reap positive learning
benefits by introducing service-learning pedagogy into a non-majors statistics course.
Key Words: Comparative study; Student project assignments; Community engagement;
Interactive applets have the ability to enhance statistics teaching by providing multiple
representations of new concepts and by facilitating experimentation. I introduce two applets
that have been developed as aids in illustrating ideas relevant to hypothesis testing and describe
how I have used these in my classes.
Key Words: Technology; p-value; Chi-square.
Students in my applied advanced statistics course for educational administration doctoral students
developed a follow-up survey for teacher preparation programs, using the following scale development
processes: adopting a framework; developing items; providing evidence of content validity; conducting
a pilot test; and analyzing data. The students developed the surveyitems by using the Interstate
New Teacher Assessment and Support Consortium (INTASC) principles as the framework to operationally
define the knowledge and skills that highly qualified teachers should possess. The students analyzed
the data from the pilot study for their final exam in the course. The follow-up survey currently
is being used by our university for program evaluation, improvement, and accreditation.
Key Words: Scale development; Applied statistics; Service learning.
Over 150 articles and book chapters were published in 2007 that pertained to statistics education.
In this column, we will 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
Teachers often get caught up in the discussion of how to teach this concept or that concept, or
how to explain this connection or that connection, but sometimes we should just stand back and be
bold enough to ask the question, "Should we even be teaching this?"; "Is it really relevant to the
modern statistics course?"; "Is it related to the GAISE guidelines?"; Do we ever use this idea
again later in our course?" As we contemplate the future of teaching statistics, it's a good time
to stop, think, and ask the hard questions. The theme of USCOTS 2009 (The United States Conference
on Teaching Statistics) is "Letting Go to Grow". In that spirit I'd like to throw out some ideas
regarding the classic 'independent vs. mutually exclusive' discussion that is still included in most
introductory statistics textbooks and in many courses.
Datasets and Stories
Data collected from Kelly Blue Book for several hundred 2005 used General Motors (GM) cars allows
students to develop a multivariate regression model to determine car values based on a variety of
characteristics such as mileage, make, model, engine size, interior style, and cruise control.
Students learn to look at residual plots to check for heteroskedasticity, normality, autocorrelation,
and multicollinearity as well as explore techniques for variable selection and develop specially
Key Words: Multiple Regression; Dummy Variables; Heteroskedasticity;
Data Transformation; Residuals.
The information for this data set was taken from a Wake County, North Carolina real estate database.
Wake County is home to the capital of North Carolina, Raleigh, and to Cary. These cities are the
fifteenth and eighth fastest growing cities in the USA respectively, helping Wake County become
the ninth fastest growing county in the country. Wake County boasts a 31.18% growth in population
since 2000, with a population of approximately 823,345 residents.
This data includes 100 randomly selected residential properties in the Wake County registry
denoted by their real estate ID number. For each selected property, 11 variables are recorded.
These variables include year built, square feet, adjusted land value, address, et al.