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Statistics

Kay Kubena

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Kay Kubena received her BS in Electrical Engineering from Rice University in 1984 and her Masters in Math Education from the University of Houston in 1989.  She currently teaches AP Statistics and PAP Precalculus at Bellaire High School in Houston, Texas, as well as serving as math department chairperson.  During her 35-year teaching career, she has taught just about every math course from Algebra 1 to BC Calculus, along with AP Computer Science.  She believes in a very high energy, hands on, activity-based approach to create engaging and challenging lessons at every level of math instruction. In 2013, she won Secondary Teacher of the Year for the Houston Independent School District and was also a finalist for Region IV Teacher of the Year for the state of Texas. Mrs. Kubena is a master teacher for the Rice University School Mathematics Project, providing quality mathematics professional development to teachers in the Houston area.  She is also a College Board consultant, offering training in PAP mathematics and AP Statistics, in both in person and on-line formats. Trainings will address content, based on the College Board’s CED, but rooted in fun activities and relevant applications.

Course Description

Our AP Statistics summer institute is a course designed for teachers who would like teaching strategies, methods, and materials on how to prepare students for success in Advanced Placement Statistics. During this week, participants will learn how to introduce challenging concepts utilizing a variety of activities and integrate technology for a more interactive classroom. In addition, teachers will collaborate together on discovery lessons, learn techniques to help students improve their technical writing, and to assess student work to prepare students for AP rigor. Participants will also explore the CED and AP Classroom to learn about all of the resources and support that the College Board provides.

Agenda

Day 1

Exploring and Understanding Data

  • Displaying and Describing Categorical Data
  • Displaying and Summarizing Quantitative Data
  • Normal Model
  • CED Overview (CB)
Day 2

Exploring Relationships Between Variables

  • Scatterplots, Association, and Correlation
  • Linear Regression Templates
  • Computer Output
  • Sampling
  • AP Classroom (CB)
Day 3

Randomness and Probability

  • Basic Probability
  • Random Variables
  • Probability Models
  • Instructional Strategies and Pedagogical Tools (CB)
Day 4

 Sampling Distributions

  • Sampling Distributions
  • Central Limit Theorem
  • Equity and Access; Diversity and Inclusion (CB)