Education Technology

2018 T³™ International Conference

March 2–4, 2018, San Antonio, Texas

T3IC Aha hero

Statistics Symposium

Saturday, March 3, 8:30 a.m. to 4:30 p.m.
Henry B. Gonzalez Convention Center, River Level, Meeting Room 005

NCTM’s “Catalyst for Change”  lays out a set of essential concepts for statistics and probability that are important for all high school graduates no matter their goals, career choices or post-high school intentions. The Statistics Symposium sessions will focus on these concepts, highlighting why they are important; giving examples that can be used in your classroom; showing how the concepts connect and build towards AP* Statistics; and illustrating how technology can be used to help students learn the concepts.

In particular, the sessions will cover:

  • Organizing data, including large data sets, into a useful and manageable structure
  • Considerations necessary to compare groups
  • Making informed decisions as part of being quantitatively literate
  • Sampling (including the role of sample size, and how samples can be used to identify typical behaviors from an unknown population)
  • The role of randomization in selecting samples
  • How simulation can be used to decide whether an outcome is surprising
In addition, the AP* Statistics Chief Reader will describe some new initiatives from the American Statistical Association to engage teachers and students in statistical activities. The day will close with a vision of what the future might be, given the advent of “big data.”

Presenters:
  • Gloria Barrett, T³™ National Instructor, Pittsboro, North Carolina
  • Ellen Breazel, Ph.D., AP* Statistics Development Committee Member, Clemson University, Clemson, South Carolina
  • Gail Burrill, Michigan State University, East Lansing, Michigan
  • Landy Godbold, T³™ National Instructor, Atlanta, Georgia
  • Deborah Nolan, Ph.D., University of California at Berkeley, Berkeley, California
  • Stephanie Ogden, Ph.D., Director, AP* Content Development – Calculus and Statistics, The College Board
  • Paul Rodriguez, AP* Statistics Development Committee Member, Troy High School, Fullerton, California
  • Jessica Utts, Chief Reader, AP* Statistics; University of California at Irvine, Irvine, California

From an Update of Statistics in the School Curriculum to the Role of Visualization in Understanding and Interpreting Data

8:30 to 10 a.m.

Presenters: Gail Burrill, Stephanie Ogden, Jessica Utts

NCTM’s forthcoming “Catalyst for Change” lays out the essential concepts for statistics that are important for all high school students no matter what their goals. The session will briefly describe these concepts and recommendations for how they might be included in the curriculum and also describe recent activities from the American Statistical Association to promote the teaching and learning of statistics in your classrooms. The major content focus will be on the role of visualization in making sense of data, beginning with the data themselves and analyzing them through the lens of “what is typical and what is not?” In particular, one emphasis will be on where these essential concepts occur in Advanced Placement®, what is important in that context and what this means for building a coherent sequence of ways of thinking beginning in earlier courses.


Activities to Introduce the Sampling Distribution

10:15 to 11:15 a.m.

Presenter: Paul Rodriguez

The sampling distribution of a statistic is all around us. We will explore several sampling activities that allow us to theorize how sample size and randomization affect the sampling distribution of a proportion or a mean. Activities include sampling from a set of beads to estimate a proportion to using Abraham Lincoln’s Gettysburg Address to estimate a mean and can be used in an algebra class to illustrate properties of graphs through AP* Statistics to develop the sampling distribution of a statistic. Hands-on manipulatives and computer applets will be demonstrated by the presenter to assist participants in developing individual strategies for (1) helping students understand how sample size effects variability and, (2) increasing students’ understanding of the typical behavior of a statistic with repeated sampling.


The Role of Randomization in Drawing Conclusions

11:30 a.m. to 12:30 p.m.

Presenter: Ellen Breazel

Students sometimes memorize what conditions are needed to perform certain inference techniques but know very little about why these conditions are important and often confuse which conditions apply to which method of inference. Through classroom activities, the session will explore gathering data through randomization and sampling distributions of statistics, in particular, the difference between random assignment and random allocation and why the distinction is important. In addition, this session will consider sampling distributions of statistics used in inference, in particular, what criteria are necessary to obtain the shape needed for inference. The presenter will assist participants in developing individual strategies for (1) helping students in their courses understand the importance of conditions for inference and, (2) increasing students’ abilities to identify the appropriate conditions for a given inference scenario.


Using Simulation to Introduce Significance Tests

1:45 to 3:15 p.m.

Presenters: Gloria Barrett, Landy Godbold

Simulation can be a powerful way to introduce the fundamental concepts of statistical significance informally. Once students have a basic understanding, they can begin to make a connection to more formal ways of dealing with significance tests. We will work through several calculator simulation activities that can be used to introduce the fundamental concepts of significance tests and to help students understand the underlying logic of the tests and the meaning of P-value.


Teaching Statistical Thinking and Practice With the Advent of Data Science

3:30 to 4:30 p.m.

Presenter: Deborah Nolan

The intuition and experience needed for sound statistics practice can be hard to learn, but the integration of statistics, computation and working with data can offer an impactful learning environment. This integrated approach creates opportunities to reinforce statistical thinking skills throughout the full data analysis cycle, from data acquisition and cleaning to data organization and analysis to communicating results. As a result, students gain the ability to reason statistically and computationally, and to actively engage in statistical problem solving. This talk describes approaches and provides examples for teaching statistics in this integrated fashion.

*AP is a registered trademark of the College Board.