Cox Mill High School
Hunter Thompson
AP Statistics
hunter.thompson@cabarrus.k12.nc.us
(704) 788-6700 ext. 2113
Classroom Guidelines / Expectations
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Obey all school-wide rules.
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Participate in class. Stay awake and alert.
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Work “bell-to-bell” on math. Do not have work for other subjects out on your desk.
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Show courtesy, respect and good manners at all times.
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Bring materials to class every day (text book, pencils, paper, homework, calculator)
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Homework will be assigned every night. Do it.
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Show integrity. Do your own work. Do not copy another person’s work or give your
work/answers to someone else.
Course Description
This AP Statistics course is taught in a 4 by 4 structured school. Our students take 4 classes each
semester on a block (90 minute) schedule. AP Statistics is offered second semester, which usually starts
the third week of January. My students are generally in class for 13 weeks prior to their exam.
Therefore, this course is taught at a brisk pace and broken into 14 chapters. During this time we will look
into and interpret graphs, calculate probability, work to understand statistical inference through
confidence intervals, as well as much more.
Materials
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Three-ring binder with notebook paper, graph paper, section dividers
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Pen, pencil, highlighter
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3 x 5 note cards
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A graphing calculator (TI-84 or TI-89) is necessary for homework and class work
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There is a course fee for stats. In lieu of me collecting this money, I will instead have you each
buy a review book.
5 steps to a 5: AP Statistics
By: McGraw Hill
Assessment / Grades
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Your performance will be evaluated through various means of assessment including tests, class
work, homework quizzes, group work, projects, and other written assignments.
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Study for tests. I never give “re-tests”, so be prepared on test day!
The AP Statistics Exam
Save the Date: May 6th or 13th
This will be the day that your statistical knowledge will be put on display, so be ready! With a good
enough score, you will receive college credit. The score needed is a 3 for most state schools.
Exam Content
The exam is three hours long and covers a one-semester introductory non-calculus-based college course
in statistics. In Section I of the exam, students are given 90 minutes to answer 40 multiple-choice
questions on a wide variety of topics. In Section II, they must answer several free-response questions;
each exam contains four to seven open-ended questions designed to be answered in about 10 minutes
each, and a longer investigative task for which 30 minutes is allotted. The following major topics are
covered:
Absences / Make-Up Work

On a day when you are absent from school, email me before noon, call a classmate, or check the
website to get your assignment.

Do your own make-up work within five days. Do not copy someone else’s work.

Copy the notes you missed from a classmate.

If you are absent on a test day, you will make up that test during class the first day you return to
school.
Discipline

Follow directions and exhibit good behavior at all times.

Failure to comply will result in parent contact, detention, referral to an administrator
Extra Help

Have integrity when working together on assignments. Ask your classmates for help, but do not
copy some else’s work or allow others to copy your work.

Tutoring will be during TEAL Time.
Class Content Details
Unit Information
Unit Name or Timeframe:
Chapter 1: Exploring Data
Time: 4 days
Content and/or Skills Taught:
• Exploring Data
• Types of Data
• Graphical Displays of Data by Type
• Graphical Displays to Include:
• Pie Chart
• Bar Graph
• Histogram
• Line Plot
• Boxplot
• Stemplot
• Dotplot
• Ogives
• Comparing Data
• Density Curves
• Standard Deviation
• Describing: Shape, Outliers, Center (mean and median), Spread (range and interquartile range,
andstandard deviation)
• Variance
• Percentiles
Major Assignments and/or Assessments:
Students will collect data of music preferences and create several graphical representations as well as
describe their data in statistical wording.
Chapter 2: The Normal Distributions
Time: 4 Days
Content and/or Skills Taught:
• Normal Distributions
• Empirical Rule
• Standard Normal Calculations
• Standardized Scores
• Assessing Normality
Chapter 3: Examining Relationships with Two-Variable Data
Time: 2 Days
Content and/or Skills Taught:
• Exploring Data
• Anticipating Patterns
• Explanatory/Response Relationship
• Causation
• Scatterplots
• Form, Direction, and Strength of a Relationship
• Correlation
• Coefficient of Determination
• Least-Squares Regression Line
• Extrapolation
• Influential Observations
• Residuals
• Residual Plots
Major Assignments and/or Assessments:
Students will retrieve data from www.olympic.org regarding the winner of a chosen event for 15
different years and the time posted for that year. They will explore the two-variable data and make
predictions.
Chapter 4: More on Two-Variable Data (Non-Linear)
Time: 4 days
Content and/or Skills Taught:
• Exploring Data
• Anticipating Patterns
• Exponential Regression
• Power Regression
• Logarithmic Transformations
• Residual Plots
• Lurking Variables
• Confounding Variables
• Causation
• Two-way Tables
• Marginal Distributions
• Conditional Distributions
• Simpsons Paradox
Chapter 5: Producing Data
Time: 4 Days
Content and/or Skills Taught:
• Sampling and Experimentation
• Designing Samples
• Designing Experiments
• Simulating Experiments
• Population
• Simple Random Sample
• Bias
• Undercoverage
• Non-response
• Stratified Random Sample
• Random Assignment
• Observational Study
• Experiments
• Factors/Explanatory Variables
• Response Variables
• Treatments
• Levels
• Experimental Units
• Placebo Effect
• Block Design
• Matched Pairs
• Double-blind
Chapter 6: Probability; Foundations for Inference
Time: 4 days
Content and/or Skills Taught:
Sampling and experimentation
Probability
• Inference
• Sample Space
• Independent Events
• Disjoint/Mutually Exclusive Events
• Venn Diagrams
• Multiplication Principle for Independent Events
• Addition Principle for Disjoint Events
• Unions
• Intersections
• Complementary Events
• Probability of Complex Events
• Conditional Probability
• Joint Probability
• Use Tree Diagrams to Solve Complex Problems with Probability
Chapter 7: Random Variables
Time: 5 days
Content and/or Skills Taught:
• Random Variables
• Sampling and Experimentation
• Discrete Random Variables
• Continuous Random Variables
• Probability Distribution Table
• Probability Histogram
• Density Curves with Probability
• Standard Normal Distribution Curves and Probability
• Mean and Variance of Discrete Random Variables
• Find Payout Values
• Law of Large Numbers
• Use Simulations and Law of Large Numbers to Approximate Mean
• Find Mean and Variances for Sums, Differences, and Linear Combinations of Random Variables
Chapter 8: The Binomial and Geometric Distributions
Time: 4 days
Content and/or Skills Taught:
• Binomial Random Variable
• Binomial Probability Tables and Histograms
• Cumulative Distribution Functions, Tables, and Histograms, for Binomial Distributions
• Calculate Means and Standard Deviations for Binomial Random Variables
• Geometric Random Variables
• Construct Geometric Distribution Tables and Histograms
• Calculate Cumulative Distribution Functions, Tables, and Histograms for Geometric Distributions
• Calculate Expected Values and Standard Deviations for Geometric Random Variables
Chapter 9: Sampling Distributions
Time: 6 days
Content and/or Skills Taught:
• Statistical Inference
• The students will be able to use Statistical Inference to draw conclusions about a population or a
process. They will be able to identify parameters of a sample or experiment, describe the bias and
variability of a statistic in terms of mean and spread, and realize that to control variability we use larger
sample sizes. Students will also work with sample proportions. They will be able to recognize when to
use p-hat, find the mean and standard deviation of a sample proportion, know that the standard
deviations/spread gets smaller as the sample size gets larger, and know when to use the normal
approximation for p-hat.
• Students will also recognize when a problem uses the mean of a sample (x-bar). They will be able to
find the mean and standard deviation of x-bar when the mean (µ) and the standard deviation (σ) are
known, know that the standard deviation of a sample distribution gets smaller as the sample size
increases, and use the central limit theorem to calculate probability for x-bar.
Chapter 10: Estimating with Confidence
Time: 7 days
Content and/or Skills Taught:
• Statistical Inference
• Students will be able to work with confidence intervals to explain statements of confidence, calculate
a confidence interval for mu and sigma, recognize when to use a confidence interval for a population
and understand the margin of error does not account for many biases, understand how the margin of
error changes with sample size and the level of confidence, and find the sample size necessary to create
a confidence interval for a specified margin of error.
• Students will also work with significance tests to state the null and alternative hypotheses as they
relate to mu, explain in simple terms the p-value when given the numerical value of p for a test,
complete a one-value z-test and the p-value for both one-sided and two-sided tests of µ, determine
statistical significance when compared to alpha, know when using a z-test is appropriate, and recognize
and explain type 1 error, type 2 error, and the power of a test.
Chapter 11: Inference for Distributions
Time: 5 days
Content and/or Skills Taught:
• Statistical Inference
• Students will be able to recognize when problem deals with inference about one mean or compares
two means and whether one-sample, matched pairs or two-sample procedures are needed.
• For one-sample procedures, students will be able to use a t-procedure to construct a confidence
interval for mu, conduct a t-test for one-sided or two-sided problems, recognize when t-tests are robust
against slight-skewness but not resistant to outliers, recognize matched-pairs design and how to
perform at t-test for these.
• For two-sample procedures, students will be able to give a confidence interval for the difference of the
means, use a t-test to determine if two populations have the same mean versus being one-sided or twosided, know when a two-sample t-test is the correct test to use.
Chapter 12: Inference for Proportions
Time: 3 days
Content and/or Skills Taught:
• Statistical Inference
• Students will be able to recognize when to use a one-sample, matched pairs, or two-sample procedure
for a study, when to use inference for a mean or proportion, and when it is appropriate to compare two
means or proportions.
• Students will be able to calculate sample proportion(s) to estimate a parameter of interest, use the zprocedure to determine the confidence interval for a sample proportion, use a z-test of significance to
test Ho: p = p0 versus one-sided or two-sided when appropriate, use a two-sample z-test to estimate the
confidence interval for p1 = p2 for two independent samples from two populations, and us a z-test to
test Ho: p1 = p2.
Chapter 13: Inference for Tables; Chi-Squared Procedures
Time: 5 days
Content and/or Skills Taught:
• Statistical Inference
• Students will be able to distinguish between and know when to use the chi-squared test of goodness
of fit, homogeneity of a population, and the test of association/independence.
• For each test, students will be able to give the appropriate null hypotheses, calculate the expected
counts, calculate the appropriate chi-squared value(s), give the degrees of freedom, use the chi-squared
critical values to approximate the p-value(s), read computer generated information to be able to draw
conclusions regarding chi-squared tests.
Chapter 14: Inference for Regression
Time: 2 days
Content and/or Skills Taught:
• Statistical Inference for Two-Variable Data
• Students will know the difference between statistics and parameters for linear relationships.
• Students will be able to find a confidence interval for the slope of a linear relationship (β), find the
standard error, and calculate the degrees of freedom.
• Students w ill be able to conduct a hypothesis test to determine if there is a relationship between two
variables including the ability to give an appropriate null hypothesis, calculate their test statistic, analyze
the results, and check the conditions.