An International Journal on the Teaching and Learning of Statistics
JSE Volume 21, Number 1 Abstracts
The purpose of this research is to better understand the role of statistics in teaching and research by faculty from all disciplines and their perceptions of the statistical preparation of their students. This study reports the findings of a survey administered to faculty from seven colleges and universities regarding the use of statistics in teaching and research with undergraduate students. The introductory statistics course serves as a foundation for statistical methods that students learn and use in classes within numerous other disciplines. Information was collected from faculty on how students can be better prepared in the introductory statistics class to use statistics in other disciplines. Findings from this paper imply that statistics is being widely used in a variety of disciplines but also suggest that cooperative communication and transitional second courses in statistics be implemented. This paper also highlights the varied statistical techniques that faculty members teach in their courses and mentor in student research projects and statistical experiences.
Key Words: Introductory Statistics; Statistics Education; Teaching; Undergraduate Research.
We investigate business undergraduate mathematics-based courses in a blended environment of online assignments and exams and offline lectures, and report the impact on academic performance of factors such as classroom attendance, web-based course supplements, and homework. We present results from both ordinary least squares and fixed effects, where the latter method controls for unobserved heterogeneity among students. We discuss biases in estimation when the ordinary least squares method is used, resulting from the fact that it ignores unobserved heterogeneity. The fixed effects results suggest that (1) class attendance has a positive impact on exam score, (2) a student who achieves proficiency in a greater number of Khan Academy skill- sets to prepare for an exam takes longer to complete an exam but does not experience a significant change in exam score, (3) a student who spends more time completing the homework spends more time completing the exam but does not experience a significant change in exam score, and (4) students who score relatively higher in homework tend to score relatively higher in exams and finish in less time than other students.
Key Words: Fixed effects; Khan Academy; Online teaching aids.
This study examines statistics instructors' use of fun as well as their motivations, hesitations, and awareness of resources. In 2011, a survey was administered to attendees at a national statistics education conference, and follow-up qualitative interviews were conducted with 16 of those (N = 249) surveyed to provide further context for interpreting the quantitative results. Motivations were similar for men and women, but female instructors admitted more hesitations in many areas. While many instructors are using or are open to using fun in the statistics classroom, the findings suggest that not having available resources at hand and not being aware of resources such as the CAUSEweb collection are major hesitations. Methods of alleviating hesitations are discussed.
Key Words: Anxiety; Cartoons; CAUSEweb Fun Collection; Games; Hesitation; Humor; Fun; Motivation; Pedagogy; Song; Statistics Education Research.
Examples are highly sought by both students and teachers. This is particularly true as many statistical instructors aim to engage their students and increase active participation. While simulated datasets are functional, they lack real perspective and the intricacies of actual data. In order to obtain real datasets, the principal investigator of a study must be willing to share the data. Understanding investigators’ opinions regarding data sharing would thus help elucidate the general lack of data sharing currently exhibited. Presented are the results of a survey designed to gather information regarding the proportion of researchers willing to share their data, conditions, formats, primary motivation, concerns and current availability of data for sharing. With 76% (56/74) responding favorably to the idea of sharing their published data, the creation of a new statistical educational resource was prompted. Thus, additionally described is a web-based dataset repository that can be used as a resource by both educators and students of statistics. This growing repository presents raw data from real medical studies and offers (a) a vignette summarizing the study, research question and study design; (b) a data dictionary with clear documentation of variables and codes; (c) a complete citation for the associated study publication; and (d) a variety of data formats compatible with the majority of statistical packages. The repository went online on 12/18/12 at the URL http://www.lerner.ccf.org/qhs/datasets/.
Key Words: Data Sharing; Teaching Examples; Educational Resource; Biostatistics; Medical Data; Clinical Trial Data; Health Data.
This article describes an applet that facilitates investigation of Simpson's Paradox in the context of a number of real and hypothetical data sets. The applet builds on the Baker-Kramer graphical representation for Simpson's Paradox. The implementation and use of the applet are explained. This is followed by a description of how the applet has been used in an introductory statistics class and a discussion of student responses to the applet.
Key Words: Simpson's Paradox; Baker-Kramer plot; Graphics.
I present an active learning classroom exercise illustrating essential principles of one-way analysis of variance (ANOVA) methods. The exercise is easily conducted by the instructor and is instructive (as well as enjoyable) for the students. This is conducive for demonstrating many theoretical and practical issues related to ANOVA and lends itself to multiple possible configurations of ANOVA results, leading to rich classroom discussion and deeper student understanding of real-world applications of the methods.
Key Words: Teaching statistics; Active learning; Activities; ANOVA; M&M's.
Recognizing the differences between three discrete distributions (Binomial, Hypergeometric and Negative Binomial) can be challenging for students. We present an activity designed to help students differentiate among these distributions. In addition, we present assessment results in the form of pre- and post-tests that were designed to assess the effectiveness of the activity. Pilot study results show promise that the activity may help students recognize the differences in these three distributions.
Key Words: Active Learning; Binomial; Hypergeometric; Negative Binomial; Project.
Interviews with Statistics Educators
Mike Shaughnessy is Professor Emeritus of Mathematics and Statistics at Portland State University in Oregon. He served as co-chair for the Board for the Special Interest Group for Research in Mathematics Education of the American Educational Research Association from 2005-2007. A member of the Board of Directors of the National Council of Teachers of Mathematics (NCTM), he served as President of NCTM from 2010-2012. This interview took place via email on November 25, 2012- February 18, 2013.
We located 30 articles that have been published from November 2012 through January 2013 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.
Many new things are going on with CAUSEweb and MERLOT, and the purpose of this short article is to share some important updates with the greater statistics education community.
Data Sets and Stories
In this paper, we report a case study that illustrates the importance in interpreting the results from statistical tests, and shows the difference between practical importance and statistical significance. This case study presents three sets of data concerning the performance of two brands of batteries. The data are easy to describe and understand, familiar to students, and allow a range of analyses, from simple to more complex. The data were the basis of a claim made in an advertisement, and this claim is re-assessed using the data to show that the company undersold the performance of their batteries from a statistical point-of-view in one of the three tests. However, a challenge is how such a conclusion can be communicated to the public succinctly but correctly.
Key Words: Real data; t-tests; Hypothesis tests; Experimental design; Practical significance.
This paper shows how the application of simple statistical methods can reveal to students important insights from climate data. While the popular press is filled with contradictory opinions about climate science, teachers can encourage students to use introductory-level statistics to analyze data for themselves on this important issue in public policy. Two detailed examples demonstrate how climate data can be a useful tool in teaching introductory statistics. The first example addresses the very important topic of the rate of decline of Arctic sea ice. Many climate scientists believe that Arctic sea ice melt is accelerating. The simple data analyses of this paper are meant to encourage students to examine the evidence themselves. The second example compares two possible explanations for the rise in global temperature over the last three decades: changes in the intensity of sunlight or changes in the concentration of atmospheric carbon dioxide. In addition to the specific data sources for these examples, the paper lists reliable on-line catalogues of climate science databases for constructing other examples.
Key Words: Simple linear regression; Multiple linear regression; Arctic sea ice.
Research on K-12 Statistics Education
A new department for the Journal of Statistics Education focused on research related to the teaching, learning, and assessment of statistics in the K-12 setting is introduced and a call for papers is made.