UCTL/Statistics

Statistics Education Research

The Application of Statistics Education Research in My Classroom

Joy Jordan - Lawrence University

Journal of Statistics Education Volume 15, Number 2 (2007)

http://http://www.amstat.org/publications/jse/v15n2/jordan.html

Various Papers

Students’ Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-leaf Plots

Linda L. Cooper and Felice S. Shore - Towson University

Journal of Statistics Education Volume 16, Number 2 (2008)

http://www.amstat.org/publications/jse/v16n2/cooper.html

Is a basketball free-throw sequence nonrandom? A group exercise for undergraduate statistics students

Stephen C. Adolph - Harvey Mudd College, California, U.S.A.

Journal of Statistics Education Volume 15, Number 3 (2007)

http://www.amstat.org/publications/jse/v15n3/datasets.adolph.html

An Active Tutorial on Distance Sampling

Alice Richardson - University of Canberra

Journal of Statistics Education Volume 15, Number 1 (2007)

http://www.amstat.org/publications/jse/v15n1/richardson.html

Trashball: A Logistic Regression Classroom Activity

Christopher H. Morrell and Richard E. Auer - Loyola College in Maryland

Journal of Statistics Education Volume 15, Number 1 (2007)

http://www.amstat.org/publications/jse/v15n1/morrell.html

The Gumball Machine: Linking Research and Practice About the Concept of Variability

M. Alejandra Sorto and Alexander White - Texas State University
Journal of Statistics Education Volume 16, Number 2 (2008)
http://www.amstat.org/publications/jse/v16n2/white.html

Y9 Level

Data Set Fun

Modeling Home Prices Using Realtor Data

Iain Pardoe - Lundquist College of Business, University of Oregon
http://www.amstat.org/publications/jse/v16n2/datasets.pardoe.html

Journal of Statistics Education Volume 16, Number 2 (2008)

It can be challenging when teaching regression concepts to find interesting real-life datasets that allow analyses that put all the concepts together in one large example. For example, concepts like interaction and predictor transformations are often illustrated through small-scale, unrealistic examples with just one or two predictor variables that make it difficult for students to appreciate how these concepts might be applied in more realistic multi-variable problems. This article addresses this challenge by describing a complete multiple linear regression analysis of home price data that covers many of the usual regression topics, including interaction and predictor transformations. The analysis also contains useful practical advice on model building—another topic that can be hard to illustrate realistically—and novel statistical graphics for interpreting regression model results. The analysis was motivated by the sale of a home by the author. The statistical ideas discussed range from those suitable for a second college statistics course to those typically found in more advanced linear regression courses.

Bus Arrivals and Bunching

R. Adam Molnar - Bellarmine University

http://www.amstat.org/publications/jse/v16n2/datasets.molnar.html

Finding suitable projects for introductory courses that blend real-world data with relevant questions and feasible instructor effort is often difficult. This paper describes one such project – tabulating the intervals between bus arrivals.

Sideline

Knowledge Surveys: An Indispensable Course Design and Assessment Tool

Karl R. Wirth - Geology Department, Macalester College, St. Paul, MN 55105 Dexter Perkins Department of Geology, University of North Dakota, Grand Forks, ND 58202

Abstract: Knowledge surveys are an indispensable tool for course design, learning, and assessment. The surveys consist of questions that cover the full breadth of content and levels of inquiry in a course. Students complete knowledge surveys at the beginning, middle, and end of a course by indicating their perceived ability to answer questions about course content. The process of developing a knowledge survey helps the instructor clarify and organize the course objectives.

During the semester the survey serves as an outline of the course and learning objectives and as a tool for helping students develop self-assessment skills. Pre-course survey data can be used to guide course content, and mid- and post-course surveys provide information about learning gains.

Comparison of knowledge survey responses, examination results, and final course grades suggests that the surveys provide meaningful measures of learning gains.

Journals

Technology Innovations in Statistics Education (TISE)

. . . reports on studies of the use of technology to improve statistics learning at all levels, from kindergarten to graduate school and professional development. The editors believe we must teach students to become data scientists who can think about and reason with data. To do this educators must employ a variety of technologies so students can better understand statistical concepts, learn to gain insight from data, and design and shape technology to meet future needs.

TISE is interested in scholarly papers that address any of these themes:

  1. Designing technology to improve statistics education
  2. Using technology to develop conceptual understanding
  3. Teaching the use of technology to gain insight into and access to data

Teaching Statistics

http://www.rsscse.org.uk/ts/

Teaching Statistics first appeared in 1979 and has been published three times a year ever since.

Teaching Statistics:

   * is for teachers of pupils aged up to about 19
   * includes articles on teaching statistics as a specialist subject and as a support tool for other disciplines.
   * is full of ideas and resources for teaching data-handling and probability.

Regular features include:

Classroom Notes; Computing Corner; Curriculum Matters; Data Bank; Practical Activities; Historical Perspective; Book Reviews; Letters; News and Notes.

SERJ - Statistics Education Research Journal

http://www.stat.auckland.ac.nz/~iase/publications.php?show=serj

SERJ is a peer-reviewed electronic journal of the International Association for Statistics Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free.