STATISTICS

Chris Olsen
COlsen@mchsi.com
Chris is a past member (twice) of the AP Statistics Test Development Committee and recently joined the 15-year club of serving as a table leader and question leader for the AP Statistics exam. After teaching statistics at George Washington High School in Cedar Rapids, IA, for over 25 years, and AP Statistics from its inception until 2007, he passed the baton.  He is now an assistant professor of Mathematics and Statistics at Grinnell College, teaching calculus, experimental design, and applied statistics classes.  He spent his undergraduate years at Iowa State University majoring in mathematics and philosophy, and in his graduate work at the University of Iowa concentrated on statistics, computer programming, psychometrics, and test development.    

He has been involved nationally and internationally in workshops and conferences mostly relating to statistics for over 35 years.   He has reviewed materials for The Mathematics teacher, the AP Central web site, The American Statistician, and the Journal of the American Statistical Association, and is on the editorial board of the Teaching Statistics journal.   He is a co-author, with Roxy Peck and Tom Short, of the Introduction to Statistics and Data Analysis, now in its 6th edition, and Statistics: Learning from Data, now in its 2nd edition.   

Current projects involve moderating the AP Statistics Teacher Community and writing computer programs to support the teaching of AP Statistics.  Since mid-March he has been sheltering-at-computer, finishing the semester online with students scattered all over the world.
Institute Overview
  
As Grizzled Veterans (Grizzlies) know, and Newbies (those first-year AP Statistics teachers we welcomed into the AP Statistics teaching community this year) have discovered, the packaging of the AP Statistics has been radically revised.  The new Course and Exam Description provides much detail to teachers and going beyond a mere “Description” of the course, offers a sound framework and resources for building quality instruction.  A bit of new content was added to the course, along with a veritable torrent of resources for teachers.  The course is now packaged into nine Units, with a huge increase in specificity and detail about what your students will be expected to know and do, all packaged in the CED. Fortunately, 95% of the content has not changed; and then there is the other 5%.  We will review the Big Ideas and the specific Skills students will need to succeed in AP Statistics, and provide information about the structure of the AP Statistics exam and the rubrics used to evaluate student responses.  We will focus on statistics as an active endeavor and present activities that will engage your students and get them “out of their seats.” The use of technology -- graphing calculators, and statistical software -- will be stressed throughout the week.  Generally, we will consider the philosophy of the course, the statistical techniques needed.   Communication – the presenting an effective argument about interpreting data -- is an essential part of doing and teaching statistics; a large part of our time together will be in discussion and interpretation, not me pontificating!  The sequence of statistical topics, and approximate allocation of time follows below.  Generally, we will focus more on the content and teaching of the course early in the week, and more on the exam and exam issues as we march through the week.
 
Online delivery
  
Covid-19 has introduced a brave new world of workshop delivery online and from a distance, presenting new challenges to presenters and participants.  This spring we had to pivot from the comfort of our classrooms to the discomfort of our homes and our students’ homes.  This summer you will be participating in a workshop not from the insulation of a college campus, but from your own homes with all the usual distractions of family life.  The consensus of a large group of AP Statistics consultants, meeting in video conference, is that workshop time should be delivered in about a 50-50 mix of synchronous and asynchronous.  The plan for me going in is to break up the day into four parts, two that would function as we would in a “normal” summer and two that would allow time away from your computers.  Specific times would surely vary with circumstances, but I am thinking of 5 six-hour days, with about 3 hours synchronous each day.  On day one I will ask for your preferences of how to break up the day and what works for your home situations.
The basic outline of the schedule
Day 1
Our first day will be a plunge into the analysis of data.  We will analyze data sets designed to highlight univariate and bivariate analysis, statistics and graphs, in the AP Statistics course.   The data sets are long on interest and are classroom ready.
•  Introduction to the Course, the course framework structure (Big Ideas, Topics, Learning Objectives.  The Calculator and Computer software (freeware provided) as basic tools.
• Unit 1: Exploring One-Variable Data.  Amphibians, Circadian rhythms, Old pottery, and that age-old question: Are snakes left-handed?
• Unit 2:  Exploring Two-Variable Data.  Categorical data (Two-way tables) and Correlation and Regression (including outliers, high-leverage points, and influence).  Gazelles, Alice in Wonderland, Therapods (e.g. T. Rex), the Beatles, and Lizzie Borden.
 
Day 2:  
On our second day we will focus on teacher issues.  We will continue our presentation of the Resources provided by the College Board:  Course development, Enrolling Students, and the “AP Classroom.”  The course content on the second day will feature Experimental Design (completely randomized design and randomized block design) and Sampling techniques (simple, stratified, cluster, systematic).  We will focus on the decisions involved in choosing an experimental design strategy, methods of control of potentially confounding variables, and what factors would lead one to particular choices of an appropriate sampling design.
• Unit 3: Collecting data – sampling and the design of experiments
• Observational studies and Experiments
• Strategies for random sampling: Simple Random Sample, Stratified, Cluster, and Systematic Sampling.  Saving apartment dwellers from noise, pedestrians from New York City traffic, and Loggerhead turtles from racoons.
• Strategies for planning experiments:  The Completely Randomized Design, the Randomized Block Design.  The logic in planning an experiment: Random selection, random assignment, and confounding.  Clam dancing, Bambi vs. the World, Fly Fishing and Slot Machines.
 
 
Day 3:
On our third day we will begin our extended discussion of the AP Statistics exam.  We will discuss the structure of the exam, how it is written, the construction and refining of rubrics, and the Reading experience.  Our content focus will be how to refine the idea of chance in statistics: Probability, Random Variables, and Sampling Distributions.
• Unit 4: Probability, Random Variables, and Probability Distributions.  Coins, Dice, the Spoon Law of Large Numbers, the likeability of coyotes, the Titanic, and Athenian democracy.
• Unit 5: Sampling distributions: Means, proportions, etc.  What is the theory, and how can we teach it via simulation?  (Hint: Statkey)
   
Day 4
We will amplify our discussion of the exam on Day 4, with primary focus the Free Response section.  What should the students write?  What does it mean to be clear, cogent, and correct?   What do the rubrics look for in student writing?  And, of course, more units.  We will begin by reviewing the general logic about hypothesis testing and estimation (confidence intervals) and then get into the nitty gritty.
• Unit 6:  Inference for Categorical Data: Proportions
• Unit 7:  Inference for Quantitative Data: Means
 
Day 5
Our fifth day will be a smorgasbord!   We will review the week so far, answer existing questions, and resolve any remaining teacher questions and content questions.  The statistical content will include our final units of inference; the exam topic will be the Investigative Task.
• Unit 8: Inference for Categorical Data – Chi square
• Unit 9: Inference for Quantitative Data -- Slopes