Webinars

Our research shows that half of the students entering a statistics course use the word random colloquially to mean, "haphazard" or "out of the ordinary." Another large subset of students define random as, "selecting without prior knowledge or criteria." At the end of the semester, only 8% of students we studied gave a correct statistical definition for the word random and most students still define random as, "selecting without order or reason." In this session we will present a classroom approach to help students better understand what statisticians mean by random or randomness as well as preliminary results of the affect of this approach.

In this webinar, I will discuss the end-of-semester project that is used in North Carolina State's introductory statistics course. This project supports statistical thinking by allowing students to apply knowledge accumulated throughout the semester. Students are presented with a research question and must design and carry out an experiment, analyze the resulting data and form a conclusion over the course of several class periods.

In introductory statistics courses, web-based applets are often used to visually conduct large simulation studies illustrating statistical concepts. However, it is difficult to determine what (if anything) students learn from repeatedly pressing a button when using applets. More advanced options such as writing/running computer code are typically considered to be much too advanced for most introductory courses. The web-based software package, StatCrunch, now offers simulation capabilities that strike a middle ground between these two extremes. The instructor/student needs only to perform a small number of steps using the menu driven interface with each step being key to understanding the underlying data structure. This talk will cover the steps required to study concepts such as the central limit theorem, confidence intervals, hypothesis testing and regression using StatCrunch.

This webinar will describe an in-class activity, motivated by Case Study 1.1.1 in The Statistical Sleuth, in which students compose haiku poems about statistics. Their poems are used to introduce two-sample t-tests and randomization tests. In addition, the in-class experiment leads to good discussion about experimental design issues, where students compare our design to the actual experiment described in Amabile et al.(1985; "Motivation and Creativity: Effects of Motivational Orientation on Creative Writers", Journal of Personality and Social Psychology 48(2): 393-399). I use this activity on the first day of our second course in applied statistics (Statistical Modeling), but it could easily be used in an introductory course as well. Examples of haiku poems which have resulted from this activity can be found at www.causeweb.org/cwis/SPT--FullRecord.php?ResourceId=1883.

This webinar will introduce several sources of data and tools that could be useful in both general and social science-specific statistics instruction. The Social Science Data Analysis Network (SSDAN) and the Inter-university Consortium for Political and Social Research (ICPSR), both a part of the University of Michigan's Institute for Social Research, are collaborating on two NSF-funded projects to support quantitative literacy in the social sciences. Resources from each organization and TeachingWithData.org, a result of the partnership, will be highlighted. Materials range from small extracts of data from the Census and American Community Surveys used with specific teaching modules to full datasets with accompanying online analysis tools.

This webinar will discuss an undergraduate Mathematical Statistics course project based on the popular video game Guitar Hero. The project included: Developing an estimator to address the research objective "Are notes missed at random?" Learning bootstrapping techniques and R programming skills to conduct hypothesis tests and Evaluating the quality of the estimator(s) under certain sets of scenarios.

This webinar will present data, tools, materials and the pedagogical approach of the Statistics Online Computational Resource (SOCR) for technology-enhanced probability and statistics education. Following a review of the different types of SOCR online resources, we will go over two specific classroom utilization examples. The first one provides a hands-on demonstration of a statistical concept (CLT) using interactive virtual experiments and simulations. The second example will showcase the use of SOCR resources to address interesting social, health, environmental, scientific, and engineering challenges. In this case, we'll focus on the Ozone pollution in California, formulate health-related hypotheses, identify appropriate data and employ web-based exploratory and statistical data analysis tools. What is www.SOCR.ucla.edu? The Statistics Online Computational Resource provides portable online aids for probability and statistics education, technology based instruction and statistical computing. SOCR tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. SOCR aims to develop new Java applets, design diverse extensible SOCR learning activities, develop XML/HTML navigation/search tools for interactive materials, and validate and assess technology-enhances pedagogical techniques. SOCR Products Tools/Applets: Distributions, Experiments, Analyses, Games, Modeler & Graphs. Multilingual instructional resources: EBooks, continuing statistics education workshops/seminars Learning activities: interactive, data-driven and technology-enhanced learning activities Examples: Central Limit Theorem Hands-on California Ozone Data Activity Data: Diverse publicly accessible datasets for copy-paste/download utilization Example: Latin Letters Frequency Distribution Dissemination: papers, conferences, workshops, etc. SOCR Evaluation and Efficacy We have conducted several control-based studies of the efficacy of technology-enhanced statistics education. Using IRB-approved studies, quantitative and qualitative measures of student performance were recorded in classes using traditional (control) instruction (R or Stata based) and classes using SOCR resources and tools. Non-parametric analyses of the data showed very statistically significant (SOCR) treatment effects (p < 10-4) on student performance and perception of the material. The practical significance of these treatment effects were more modulated. More details about these studies are available here. Summary Main SOCR server, applets Data, activities and EBooks Feedback and Forum Graphical SOCR Navigator

Educational games have had varied success in the past. However, what it means to incorporate games into the classroom has changed dramatically in the last 10 years. The goals of our games are to 1) foster a sense of engagement, 2) have a low threat of failure, 3) allow instructors to create simplified models of the world around us, and 4) motivate students to learn. This webinar will use the same reaction time game to demonstrate a simple 1- 2 day activity that is appropriate for introductory courses as well as an advanced project that encourages students to experience data analysis as it is actually practiced in multiple disciplines. In the introductory activity students are asked to spend 15 minutes playing an on-line game. Data collected from the game is used to demonstrate the importance of proper data collection and appropriate statistical analysis. The advanced project asks students to read primary literature, plan and carry out game based experiments, and present their results.

This year, Jeanne and Bill assumed co-editorship of the Chance News Wiki, which as of March 15 will be moving to CAUSEweb. The Wiki provides reviews of current news stories that are relevant to teaching statistics and probability, along with links to original articles and related resources. This webinar will describe the various ways that Chance project materials have been used, in areas ranging from traditional introductory statistics to statistical literacy courses to first-year seminars. We will also discuss the mechanics of posting to the Wiki, and hope to inspire some new contributors.

This is a CAUSE Special Presentation for USCOTS Research Cluster members.