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  • Is Stats 101 prepared for the CC Student?

    Jerry Moreno, John Carroll University
    Tuesday, May 10, 2011 - 2:00pm
    Forty-three states have signed on to the mathematics part of the Common Core State Standards (CC). Statistics and Probability play a prominent part in CC grades 6-11 for all students. How may Stats 101 have to change to accommodate potentially better prepared quantitatively literate students?
  • The Role of a Wine Pricing Competition in Teaching Data Mining at Stanford

    Susan Holmes & Nelson Ray, Stanford University
    Tuesday, April 26, 2011 - 12:00pm
    We will discuss how we coordinated, held, and judged a wine pricing competition (hosted on Kaggle-in-Class - to engage students in applying prediction techniques learned in our data mining class at Stanford. We found that with proper incentives, the competition was very successful in getting students interested in working collaboratively in a race against the clock to eke out additional predictive performance in their models.
  • Eat Less Salt, Drink More Wine, Dump The Cellphone, Eat More Salt, And Live Longer: Teaching Students To Understand The Role Of Data Collection In Statistical Inference

    Rob Gould, UCLA
    Tuesday, April 12, 2011 - 2:00pm
    The role that data collection plays in causal inference is of fundamental importance in introductory statistics, and yet is outside the comfort zone for many of us. In this webinar, I'll discuss why causal inference is important and also fun, and give some advice for teaching this topic.
  • What Proportion Of The U.S. Is Within A Mile Of A Road?

    Nicholas Horton, Smith College
    Tuesday, March 22, 2011 - 12:00pm
    A challenge in introductory statistics is to motivate the estimation of unknown population parameters. In this activity, we allow students to estimate the proportion of the continental United States that is within a mile of a road by repeatedly sampling latitudes and longitudes and viewing that location using an internet mapping service. Technology is used to generate random values within a specified geographic rectangle, which populate a data collection spreadsheet. Students are instructed how to use to determine if the random location is within the continental US and if so, whether it is within a mile of a road. This data collection task helps to fix ideas of study design ("what if the point lands in the middle of one of the Great Lakes"?) as well as motivate the estimation of an unknown proportion. Individual confidence intervals can be created and compared, as well as creation of a class-wide confidence interval. This activity can be used in introductory classes at all levels.
  • To Teach Statistical Inference, Try Standing On Your Head

    Cliff Konold, Director, Scientific Reasoning Research Institute, University of Massachusetts Amherst
    Tuesday, March 8, 2011 - 2:00pm
    Generally in learning statistical inference, students reason backwards from data to the (usually invisible) process that produced them. I will demonstrate an alternative approach in which students begin at the process end, designing their own "data factories." Based on their output, students modify their factories such that, for example, a collection of cats produced by a cat factory has features that look more like real cats. This work is part of the NSF-funded "Model Chance" project. In this project, we have been adding probability modeling to the existing data-visualization capabilities of TinkerPlots and, using that environment, exploring how data and chance might be better integrated in our instruction beginning in the middle school.
  • FREE CLICKERS!: Using PollEverywhere for Formative Assessment in the Classroom

    Michael Posner, Villanova University
    Tuesday, February 22, 2011 - 2:30pm
    Formative assessment is where feedback on learning activities is used to modify the method of teaching to meet the needs of the learner. One such strategy is the use of personal response systems, or clickers, for instant feedback. Immediately examining the responses, teachers transcend the lecture-only model and are empowered to foster student-centered learning by explaining misconceptions or feeling confident that students understand the concepts. Attention is no longer deferred to the loudest student or the fastest hand-raiser, but rather to entire class. I have wanted to try clickers, but was reluctant due to the barriers of implementation - cost to the student and software and hardware demands, including students forgetting their clickers. I recently discovered, which allows students to text in their answers using cell phones and see the results immediately on the screen. Results can be captured and shared with students on websites or blogs. It's free for small classes and claims to cost 1/3 as much as clickers for larger classes. My students love it! I'll discuss my experiences and share how I have integrated some of the classic active-based exercises in statistics into my class and used formative assessment techniques that have helped bring my classroom to life. Have your cell phones ready if you join this webinar!
  • Building a Statway to Heaven

    Uri Treisman, Director, Charles Dana Center, University of Texas at Austin
    Tuesday, February 8, 2011 - 2:00pm
    Developmental education in America's community colleges has been a burial ground for the aspirations of our students seeking to improve their lives through education. Under the leadership for the Carnegie Foundation for the Advancement of Teaching and the Charles A. Dana Center, nineteen community colleges and systems are building accelerated pathways to and through developmental education with the goal of helping students with low levels of mathematical preparation complete a college credit bearing, transferable statistics course within one year. Uri will describe the work to date, the challenges the initiative faces, and the underlying ideas of improvement science that are driving its development.
  • Golfballs In The Yard - Using Simulation To Teach Hypothesis Testing

    Randall Pruim, Calvin College
    Tuesday, January 25, 2011 - 2:30pm
    One challenge in any introductory statistics course is helping our students understand the logic of hypothesis testing. In this webinar I'll demonstrate one of my favorite examples for doing this. The data are a sample of golfballs. The hypothesis is that the number on a golfball is equally like to be a 1, 2, 3, or 4. Using a function written in R, I allow students to design their own test statistics and then produce a graphical display of the sampling distribution and calculate empirical p-values. This activity can be used in introductory classes at all levels - even if you don't cover goodness-of-fit testing. It can be used as a first introduction to inference, as a motivation for the chi-squared test statistic, as an example of goodness of fit testing, or as a demonstration of simulation-based inference.
  • Introducing Informal Inference Using Data-Centric Lab Exercises

    Rakhee Patel, UCLA
    Tuesday, January 11, 2011 - 2:00pm
    Since formal hypothesis testing and inference methods can be a challenging topic for students to tackle, introducing informal inference early in a course is a useful way of helping students understand the concept of a null distribution and how to make decisions about whether to reject it. We will present two computer labs, both using Fathom, that illustrate these concepts using permutation in a setting where students will be answering interesting investigative questions with real data.
  • Facilitating Student Projects in Statistics

    Dianna Spence & Brad Bailey, North Georgia College & State University
    Tuesday, December 14, 2010 - 2:00pm
    When instructors have their students implement "real-world" projects in statistics, a number of questions arise: Where can students locate real data to analyze? What kinds of meaningful research questions can we help students to formulate? What aspects of statistical research can be covered in a project? What are reasonable methods for evaluating the student's work? The presenters will share resources developed during an NSF-funded study to develop and test curriculum materials for student projects in statistics, using linear regression and t-test scenarios.