# Webinars

• ### Sampling Variability: A hot topic in the Common Core

Anna Bargagliotti (for the Project-SET team), Loyola Marymount University
Tuesday, June 10, 2014 - 12:00pm ET
The Common Core State Standards (CCSS) include much more statistics content than previous standards. Their adoption has created the opportunity and necessity for nearly all middle school and high school mathematics teachers to be prepared to teach a substantial amount of statistics. This session will focus on the topic of sampling variability, a topic that is greatly emphasized in the middle and high school grades in the CCSS. We will present a research-based learning trajectory to help guide teacher preparation on this topic. In addition, we will discuss several unexpected misconceptions that emerged while testing the trajectory with high school teachers. As a group, we will work through an activity together to illustrate how to use the trajectory with teachers.
• ### Does eye color depend on Gender? It Might Depend on Who or How you Ask

Amy G. Froelich, Iowa State University
Tuesday, April 15, 2014 - 12:00pm ET
As a part of an opening course survey, data on eye color and gender were collected from students enrolled in an introductory statistics course at a large university over a recent four year period. Biologically, eye color and gender are independent traits. However, in the data collected from our students, there is a statistically significant dependence between the two variables. In this article, we present two ideas for using this data set in the classroom, and explore the potential reasons for the dependence between the two variables in the population of our students.
• ### The Evidence for Efficacy of HPV Vaccines: Investigations in Categorical Data Analysis

Alison Gibbs & Emery Goossens, University of Toronto
Tuesday, March 18, 2014 - 12:00pm ET
Our current students are among the first to have been vaccinated against HPV. Have they ever considered how the accumulation of the evidence for the efficacy of the vaccine resulted in recommendations for its widespread provision? Using data sourced from a meta-analysis of clinical trials for HPV vaccines, we will examine this evidence. We will show how these data can be used to illustrate applications of methods of categorical data analysis, for students in courses at a variety of levels. And we will describe how this case study can be used to promote discussion of concepts in the design of experiments, statistical concerns such as independence of observations, and the importance of context in the interpretation of the results of data analyses.
• ### Developing New Statistics Instructors and Student Leaders Through Peer Mentoring

Aimee Schwab & Erin Blankenship; University of Nebraska, Lincoln
Tuesday, March 11, 2014 - 4:00pm ET
Like many other research universities, the University of Nebraska-Lincoln relies on graduate student instructors to cover a large portion of the instructional load in the introductory course. In order to better prepare new graduate student instructors, we have implemented a mentoring program that pairs new GTAs with experienced graduate student instructors. Through the mentoring program, the new GTA has a semester to acclimate to graduate school and their new role as instructor, and the senior GTA has the opportunity to emerge as a teacher leader.
• ### Five Years on the Island

Michael Bulmer, University of Queensland
Tuesday, February 25, 2014 - 3:00pm ET
The Island (island.maths.uq.edu.au) is an online virtual population to support learning and teaching in experimental design, epidemiology and statistical reasoning. This month the Island is celebrating five years since the switch was flicked and the population came to life. In this presentation we will give some examples of how the Island has been used in those five years and suggest some activities for you to try.
• ### Discovery Projects in Statistics: Implementation Strategies and Examples of Student Projects

Brad Bailey & Dianna Spence, University of North Georgia
Tuesday, February 18, 2014 - 12:00pm ET
In this presentation we will discuss student-directed discovery projects in statistics, which are intended as the means through which statistical content is taught to the students. In particular, we will delineate the purpose and scope of a project covering linear regression analysis and another project covering comparisons with basic t-tests. We will describe curriculum materials developed to help instructors facilitate such projects and provide the web address where these materials can be accessed. We will give examples of how instructors use the curriculum materials to guide students through the projects' stages. In particular, the materials can be used to provide the students with clear information about the project requirements and what activities the students are expected to be engaged in during each phase of the student-directed projects. These projects are truly student-directed in that the students select their own research topic, define their own variables, and devise and carry out their own data collection plan before analyzing and interpreting their data. The students report their results in two forms: a written report is provided to the instructor and a brief formal presentation is made before the rest of the class. In both formats, the students report the findings of their research project, as well as explain why they chose the particular research topic, explain how they gathered, organized and analyzed the data and list any short-comings they perceive in their own project. Our presentation will include specific examples of projects that students have conducted. Finally, we will also discuss the rationale for assigning such projects, including the potential benefits of such projects - benefits suggested by both prior and on-going research - and possible factors mediating those benefits.
• ### Strategies for successful implementation of collaborative student assessment in face-to-face and online statistics classes

Audbjorg Bjornsdottir, University of Minnesota
Tuesday, February 11, 2014 - 12:00pm ET
This presentation will be about collaborative tests, where students are allowed to work together during the exam. It will include a review about the effectiveness and different formats of collaborative tests along with successful strategies for implementing them in face-to-face and online statistics classes.
• ### Primarily Statistics: Developing an Introductory Statistics Course for Pre-service Elementary Teachers

Jennifer L. Green, Montana State University and Erin E. Blankenship, University of Nebraska-Lincoln
Tuesday, January 21, 2014 - 3:30pm ET
We developed an introductory statistics course for pre-service elementary teachers. In this webinar, we will describe the goals and structure of the course, as well as the assessments we implemented. Overall, the course aims to help pre-service teachers recognize the importance of statistics in the elementary curriculum, as well as the integral role they, as teachers, can play in a student's entire statistical education.
• ### Investing in the Next Generation through Innovative and Outstanding Strategies (INGenIOuS): Report of outcomes from a recent workshop

A. John Bailer, Miami University
Tuesday, January 14, 2014 - 12:00pm ET
The need for a larger proportion of the workforce to enter well equipped with mathematics and statistics skills has been acknowledged in a number of recent reports. To address this need, action must be taken by all stakeholders involved in preparing students for 21st century workforce demands. A collaboration of mathematics and statistics professional societies recently culminated in a workshop focused on identifying strategic steps that might be taken to dramatically increase the flow of mathematical sciences professionals into the workforce pipeline.
• ### Does My Baby Really Look Like Me? Using Tests for Resemblance to Teach Topics in Categorical Data Analysis

Amy G. Froelich & Dan Nettleton, Iowa State University
Tuesday, November 19, 2013 - 12:00pm ET
Many new parents have heard claims of a striking resemblance between them and their babies. As parents ourselves, we were skeptical of such claims so we devised a study to objectively answer the question "Does my baby really look like me?" In this webinar, we will present a study to test whether neutral observers perceive a resemblance between a parent and a child. We will demonstrate the general approach with two parent/child pairs (Amy and her daughter and Dan and his son) using survey data collected from introductory statistics students serving as neutral observers. We will then present ideas for incorporating the study design process, data collection, and analysis into different statistics courses.