The primary goal of this institute is to familiarize participants with the entire AP Statistics curriculum. To achieve that goal, topics will be covered under the following tentative schedule.

July 17 July 18 July 19 July 20 (half day)

It is my sincere hope that participants will not only become fluent in use of statistical techniques but gain an understanding of the underlying principles of those techniques. It is highly likely that most students will take the AP exam upon completion of the course. To help insure student success on the exam, a secondary goal of this institute is to provide participants with a basis to evaluate the progress of their students in terms of the exam expectations, especially for free response questions. I believe the best means of conveying exam expectations is by analyzing previous exams. Therefore, I will provide a detailed description of the expectations from the 2017 and 2018 constructed response questions which will be imbedded appropriately in sections of the PowerPoint presentations. All participants will receive a thumb drive containing all PowerPoint presentations, electronic versions of all handouts, and many other documents as well.

I encourage participants to bring the graphing calculator that you most likely will be using when you teach the course. The reason for this is obvious. In addition, I will be bringing Casio Prism graphing calculators for participants to use during many of the activities conducted in the institute. The reason for this is far less obvious. Many of the activities involve lists (some of which are rather long) and matrices. Rather than have participants input the data in their personal calculator, I will have stored approximately 80 lists (some of which vary for activities where the class is subdivided into six unique groups) and a half-dozen matrices that will be used. Participants should have no trouble using this calculator even if they are not familiar with it because all necessary instructions are imbedded the PowerPoint presentations.


Topics will include:

  • Displaying and Exploring Data
    • Categorical data
      • Bar graphs
      • Segmented bard graphs
        • By counts
        • By percentages
      • Circle graphs
    • Quantitative data
      • Histograms
      • Box plots
      • Normal probability plots
      • Scatterplots
    • Summary statistics
    • Arithmetic manipulations and their effect on summary statistics
  • Probability and Simulation
    • General probability terms
    • General probability rules
    • Discrete random variables
      • Mean and standard deviation
      • Binomial distributions
        • Mean and standard deviation
        • Calculation of probability for an exact value
        • Calculation for the probability of a range of values
        • Inverse binomial calculations
      • Geometric distributions
        • Mean and standard deviation
        • Calculation of the probability of an exact value
        • Calculation of the probability of a range of values
    • Normal distributions
      • Standard Normal distributions
      • Other Normal distributions
      • Calculation of the probability of a range of values
      • Inverse Normal calculations
  • Linear Regression
    • Summary values: informative or not?
    • Correlation versus causation
    • Why the correlation coefficient is applicable only to linear models
    • Interpolation versus extrapolation
    • Effects on correlation
      • Arithmetic manipulations of data
      • Interchanging explanatory and response variables
      • Nonarithmetic manipulations
    • Using technology to calculate least squares regression (LSR) models
    • Interpreting slopes in context
    • Interpreting y-intercepts in context
  • The Basics of Inference Procedures
    • Meaning of confidence intervals
    • Correct and incorrect interpretations of confidence intervals
    • Constructing confidence intervals
      • Point estimates
      • Critical values
      • Margins of error
        • Calculating margins of error
        • Using margins of error to calculate other related variable values
    • Meaning of hypothesis tests
    • Null and alternative hypotheses
    • Significance levels
    • P-values
    • Decisions
    • Conclusions
  • Inference for Categorical Data: One Proportion
    • Confidence intervals
    • Hypothesis tests
  • Inference for Quantitative Data: One Mean or One Slope
    • Confidence intervals
    • Hypothesis tests
    • Relationships between confidence intervals and hypothesis tests
    • Relationships were not discussed for categorical data. Why was that the case?
  • Inference for Differences (categorical and quantitative data) and Paired Differences (quantitative data)
    • Confidence intervals
    • Hypothesis tests
    • Relationships between confidence intervals and hypothesis tests (quantitative data only)
  • Inference for Multiple Comparisons: The Chi-Square Tests
    • Goodness of fit (GOF)
    • Two-way tests
    • Arithmetic manipulations of data and their effect on results/conclusions
  • Discussions of 2017 and 2018 free response questions will occur as they are pertinent to the topics being discussed.
  • Closing presentation: Why (I believe) all students should study statistics

Participants are invited to send questions or concerns directly to Jeanne Lorenson at

Excellent coverage of AP materials for exam.

–Past Client

Ken Pendleton

Ken Pendleton began teaching Statistics in 1995, and in the spring of 1997 my students took the very first AP Statistics exam. A seminal event in the development of my ability to teach AP Statistics was my attendance at an AP Statistics Institute in the summer of 1997. With the encouragement of the leader of that institute, I applied to become a reader of the exam and completed the typical six-year high school rotation, serving in the summers of 2000 through 2005. During that time the College Board invited me to apply to become a leader of AP Statistics workshops. I have conducted workshops and summer institutes for the last fifteen years, and I managed to find time to complete my Masterís Degree in Measurement and Statistics at the University of Maryland in May of 2006. That degree enables me to teach Statistics as an adjunct faculty member at the Germantown branch of Montgomery College, which I have done for the past eleven years, and serve as a college reader of the exam, which I have done for the past seven years. In all, I have read more than half of all AP Statistics exams given.

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Institute Faculty

The faculty have been selected for their teaching expertise, creativity, innovations in teaching and experience with the AP* Program curriculum. All faculty members are endorsed and certified by the Middle Atlantic Regional Office of The College Board and have demonstrated a commitment to excellence that is second to none.

Daily Schedule

Classes are scheduled from Tuesday - Friday, 7:30 a.m. - 3:30 p.m.

Class check-in begins at 7 a.m. with as brief orientation at 7:20 a.m.

Participants receive a catered lunch at a waterfront restaurant each day.

Morning and afternoon coffee/snack breaks are provided each day.

An Opportunity for Learning and Interacting

Instructors encourage sharing among participants that will enhance the knowledgeand skills of all participants for effective teaching. The opportunity to exchange and communicate with instructors and colleagues within the Middle Atlantic Region and beyond is a valued support resource for the entire school year.

Course Questions?

Questions/concerns about your particular course can be addressed by going to course description and clicking on the instructor’s name. You will then be able to e-mail the instructor. Any problems call the Lewes Summer Institute office at 302-644-0277.

* This Summer Institute has been endorsed by Advanced Placement Program, AP, Pre-AP, College Board and it’s logo are registered trademarks of the College Board.