Webinars

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.

This paper describes a textbook -development paradigm that has the flexibility to meet the specific needs of a department, college, and surrounding business community, while simultaneously lowering costs for students, facilitating the transition from intro-level to mid- and upper-level courses, preserving professor-specific preferences over course content and structure, increasing the quality and uniformity of the curriculum, overcoming difficulties of traditional rental programs, enhancing the professional development and teaching ability of professors, and improving student learning outcomes.

Undergraduate study of statistics has been growing in recent years, with the number of students completing stats majors in the United States doubling in the past 5 years. At the same time, the amount and complexity of data being collected increases almost without bound. What should students completing undergraduate majors, minors or concentrations in statistics learn in order to help analyze this flood of information? The American Statistical Association endorsed guidelines in this area in 2000, and a workgroup is now considering what needs to be changed and amplified from the earlier report and supporting materials. In this webinar, participants will hear more about the process, learn about and identify key issues to be considered, and have the opportunity to make suggestions about areas and topics to explore.

There has been an increasing number of school systems which are being held accountable for student performance, however there has not been a corresponding emphasis on school and teacher preparation with which to achieve these standards. Previous studies have shown the variation in teacher preparation both within and between countries. Many studies have shown that teachers are a major factor in predicting student achievement and academic success (Hattie 2008). And yet, to date there has been a lack of cross-national focus on the preparatory programs of educators and available data is sparse. I would like to help bring new attention to the importance of quality teacher training. My paper provides a broad comparison of national education systems, including teacher preparation requirements. I explore this topic by analyzing the performance of students in over 50 countries who participated in the 2006 and 2009 PISA (Program for International Student Assessment). I will demonstrate that high-quality teacher training is related to student achievement and learning and suggests that improving teacher training might contribute to local and national growth and development.

In this webinar I will discuss the development and assessment of an activity used in an introductory calculus-based statistics course to distinguish between these three discrete distributions. Students from the assessment were students in one of these courses.

"Which Traits Attract Women: Appearance, Intelligence, Wealth, or Strength?" was the first place winner of the Undergraduate Statistics Class Project Competition. Project mentor, Nathan Tintle of Dordt College, will briefly discuss the class assignment underlying the project and how he handles the project and the competition. Joshua Nymeyer, Dordt College, the team leader from the this class project will present their work.

This webinar will describe the motivation and summarize the major points of a recently released report on connecting research and practice in statistics education. The report seeks to foster productivity and coherence in statistics education research by providing a portal to the statistics education literature, guidance on important priorities in the field, and the impetus for development and wide use of instruments needed to address fundamental questions in the field.

We have developed a set of freely available web-based apps called StatKey (lock5stat.com/statkey) for supporting statistics courses that use modern simulation methods (such as bootstrap intervals and randomization tests) to introduce the core ideas of statistical inference. In this webinar we demonstrate the main features of StatKey and discuss how it can be used to make these methods easily accessible and understandable for students with a wide variety of backgrounds. Although StatKey's built-in examples are coordinated with the Wiley text Statistics: Unlocking the Power of Data, the tools allow students and instructors to input and analyze their own data and can be used with any course seeking to give students experience with what many people call the "next big thing" in statistics education.

In this webinar, we discuss the rationale and results for an exploratory survey on (N = 249) statistics instructors' use of fun, including their motivations, hesitations, and awareness of resources. Respondents were attendees at the 2011 United States Conference on Teaching Statistics and 16 completed phone interviews after the conference.

Our presentation will highlight the needs in statistics education from the perspective of client disciplines based on the use of statistics in teaching and research in various academic affiliations. This information will cultivate discussion on how to use the information to guide curriculum development in introductory statistics. As a result of this study, a large data set was compiled that can be used in the classroom for students to explore. A demonstration of how to access and use the data set in class will be given.