An International Journal on the Teaching and Learning of
JSE Volume 23, Number
Can individuals guess the gender of a writer based on a sample of his or her handwriting? We administer an electronic survey twice to the same individuals to find out. The resulting data set is interesting to students, rich enough to be amenable to a wide array of activities, and open to a variety of exploratory tacks for statistics students and teachers.
Key Words:Handwriting analysis; Gender; Data project.
The purpose of this research study was to learn about students’ conceptions concerning the line of best fit just prior to their introduction to the topic. Task-based interviews were conducted with thirty-three students, focused on five tasks that asked them to place the line of best fit on a scatterplot and explain their reasoning throughout the process. The results include descriptions and categorizations of students’ meanings, criteria and methods for placement, accuracy of placement, and interpretation of the line of best fit. The discussion addresses how students’ prior study of mathematics and statistics impacted their conceptualizations of the line of best fit as well as implications for the teaching and learning of the line of best fit.
Key Words:Statistics Education; Statistical Association; Linear Regression.
Web-augmented traditional lecture, fully online, and flipped sections, all taught by the same instructor with the same course schedule, assignments, and exams in the same semester, were compared with regards to student attitudes; statistical reasoning; performance on common exams, homework, and projects; and perceptions of the course and instructor. The Survey of Attitudes Toward Statistics-36 (SATS-36) instrument and eight questions from the Statistical Reasoning Assessment (SRA) were given both at the beginning and end of the semester to measure change. The students selected their own sections, but the students in the sections were similar demographically, with similar pre-course college grade point averages. The SATS-36 showed increases in affect, cognitive competence, and perceived easiness and decreases in value, interest, and effort from beginning to end of the semester for all sections. Only affect and perceived easiness showed any differences for section, with traditional higher than online on average for both. Results from the SRA questions showed an increase in correct statistical reasoning skills and decrease in misconceptions for all sections over the semester. Traditional students scored higher on average on all three exams, but there were no significant differences between sections on homework, the project, or on university evaluations of the course or instructor. Results are contextualized with prior educational research on course modalities, and proposals for future research are provided.
Key Words:Attitudes toward statistics; Blended; SRA; SATS-36; Flipped classroom; Statistical reasoning; Technology-enabled statistics education; Statistical literacy.
Previous mathematics and science education research indicates that knowledge and beliefs, including teaching efficacy, affect teachers’ actions and effectiveness in a classroom. Our middle grades and high school Self-Efficacy to Teach Statistics (SETS) instruments, aligned with the statistical concepts in national and state guidelines such as the GAISE Pre-K-12 Report and the Common Core State Standards for Mathematics (CCSSM), were developed for use in teacher education research. This study focuses on the middle grades SETS instrument, which measures pre-service teachers’ self-efficacy to teach topics at GAISE levels A and B as well as K–8 CCSSM statistics topics. The items ask teachers to rate their self-efficacy to teach a particular concept on a Likert scale from 1 (“not confident at all”) to 6 (“completely confident”). Data were collected at four public institutions of higher education in the United States. Rasch modeling was used to order the items by difficulty of endorsement to gain knowledge regarding pre-service teacher perceptions of difficulty, with the goal of identifying priorities for increasing pre-service teachers’ self-efficacy with statistical topics.
Key Words: SETS instrument; GAISE; Common Core State Standards for Mathematics (CCSSM); Pre-service teachers; Middle grades.
Roger W. Johnson, Donna V. Kliche, and Paul L. Smith
Modeling Raindrop Size
Being able to characterize the size of raindrops is useful in a number of ?elds including meteorology, hydrology, agriculture and telecommunications. Associated with this article are data sets containing surface (i.e. ground-level) measurements of raindrop size from two different instruments and two different geographical locations. Students may begin to develop some sense of the character of raindrop size distributions through some basic exploratory data analysis of these data sets. Teachers of mathematical statistics students will find an example useful for discussing the beta, gamma, lognormal and Weibull probability density models, as well as fitting these by maximum likelihood and assessing the quality of fit. R software is provided by the authors to assist students in these investigations.
Key Words: Distribution; Exploratory Data Analysis; Parameter Estimation; Maximum Likelihood; Disdrometer; Beta Density; Exponential Density; Gamma Density; Lognormal Density; Weibull Density.
Statistics courses that focus on data analysis in isolation, discounting the scientific inquiry process, may not motivate students to learn the subject. By involving students in other steps of the inquiry process, such as generating hypotheses and data, students may become more interested and vested in the analysis step. Additionally, such an approach might better prepare students to tackle real research questions outside of the statistics classroom. Presented here is a classroom activity utilizing the popular Hasbro board game Operation, which requires student involvement in the entire research process. Highlighted are ways this activity uncovers a number of research issues. A number of categorical and continuous variables are collected, making the activity amenable to a variety of statistical investigations and thus easy to imbed into any curriculum. Designed to mimic a real-world research scenario, this fun activity provides a guided yet flexible research experience from start to finish.
Key Words: Teaching Statistics; Active Learning; Activities; Student-generated Data;
This study aimed to quantify the influence of student attributes, coursework resources, and online assessments on student learning in business statistics. Surveys were administered to students at the completion of both online and on-ground classes, covering student perception and utilization of internal and external academic resources, as well as intrinsic motivating factors for success in the course. Student performance as defined by quality points, various assignment points, and time spent on assignments, was not significantly different between on-ground and online students. However, use of resources and tools to complete homework and learn new topics differed. As a whole, students predominantly utilized homework as the first tool to learn new topics and complete homework, suggesting a paradigm shift in the way instructors should cater to student’s learning habits.
Key Words: Online assessment; Homework manager; Learning preferences.
This paper introduces a dataset and associated analysis of the scores of National Football League (NFL) games over the 2012, 2013, and first five weeks of the 2014 season. In the face of current media attention to “lopsided” scores in Thursday night games in the early part of the 2014 season, t-test results indicate no statistically significant difference between the winning margins in Sunday games vs. Thursday games during the 2012 and 2013 seasons. Interestingly, there is a statistically significant difference between the Sunday vs. Thursday game margins over the first five weeks of the 2014 season. Moreover, statistical process control methods suggest an “out of control” condition for Thursday night game margins during the first five weeks of the 2014 season. The exercise provides students with an opportunity to apply a variety of hypothesis testing and graphical analysis tools to a question of current interest in the popular media.
Key Words: t-test, Time series, Statistical process control.
with Statistics Educators
George Cobb is Professor Emeritus of Mathematics and Statistics at Mount Holyoke College. He is a Fellow of the American Statistical Association and a recipient of ASA’s Founders Award. He received the USCOTS Lifetime Achievement Award in 2005. The following interview took place via email on December 30, 2014 – February 17, 2015.
I located one special journal issue and 32 total articles that have been published from November 1, 2014 through March 15, 2015 that pertained to statistics education. In this column, I highlight a few of these articles that represent a variety of different journals that include statistics education in their focus. I also provide information about the journals and a link to their websites so that abstracts of additional articles may be accessed and viewed.
The aim of this short column is to provide an overview of resources and events from CAUSEweb (www.causeweb.org) and MERLOT (www.merlot.org) to help you stay connected with the Statistical Education community.