ORANGE COUNTY HIGH SCHOOL OF THE ARTS
AP Statistics Course Outline
There is no summer assignment for AP Statistics. Please read this information to prepare you for the
expectations of the course.
Course PURPOSE/Goals
The purpose of this course is to introduce students to the major concepts and tools for collecting, analyzing, and drawing
conclusions from data. Students are exposed to four broad conceptual themes:
1. Exploring Data: Describing patterns and departures from patterns (SIA CH.2 & 3)
2. Sampling and Experimentation: Planning and conducting a study (SIA Ch. 4)
3. Anticipating Patterns: Exploring random phenomena using probability & simulation (SIA Ch. 5, 6)
4. Statistical Inference: Estimating population parameters and testing hypotheses (SIA Ch. 7-11)
It is the expectation of the instructor that you plan to take the A.P. test in the spring.
COURSE Materials
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Primary Textbook (in class daily):
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Supplemental Textbooks (optional):
 Moore, David S., and George McCabe. Introduction to the Practice of Statistics. W.H. Freeman &
Company; 5th ed. (February 2005). (IPS)
 Bluman, Allan G. Elementary Statistics: A Brief Version. McGraw-Hill Science/Engineering/Math; 3 ed.
(January 1, 2006) (ESBV)
 Gonick, Larry, and Woollcott Smith. A Cartoonist Guide to Statistics. Harper Resource (1993) (TOON)
Graphing Calculator (in class daily): TI-83, TI-84, TI-85, or TI-86 (TI)
Software: Access to Microsoft Excel (home as well as in the computer lab) (IMMRC)
Course OUTLINE
In the following course outline you will find the key topics, questions to be completed from the text, project assignments,
supplementary information, and assessments that are organized by units of study. The ordering here is intended to define
the scope of the course but not necessarily the sequence. The percentages in parentheses for each content area indicate
the coverage for that content area of the exam.
UNIT 1 – Exploring the Data: Describing patterns and departures from patterns (20%-30%) Exploratory analysis of
data makes use of graphical and numerical techniques to study patterns and departures from patterns. Emphasis should
be placed on interpreting information from graphical and numerical displays and summaries.
Constructing and interpreting graphical displays of distributions or univariate data (dotplot, stemplot, histogram,
cumulative frequency plot)
Center and Spread
Clusters and Gaps
Outliers and other unusual features
Shape
Summarizing distributions of univariate data
Measuring center: mean, median’
Measuring spread: range, interquartile range, standard deviation
Measuring positions: quartiles, percentiles, standardized scores (z-scores)
Using boxplots
The effect of changing units on summary measures
Comparing distributions of univariate date (dotplot, back-to-back stemplot, parallel boxplot)
Comparing center and spread: within group, between group variation
Comparing clusters and gaps
Comparing outliers and other unusual features
Comparing shapes
Exploring bivariate data
Analyzing in scatterplots
Correlation and linearity
Least-squares regression line
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ORANGE COUNTY HIGH SCHOOL OF THE ARTS
AP Statistics Course Outline
Residual plots, outliers and influential points
Transformations to achieve linearity: logarithmic and power transformations
Exploring categorical data
Frequency tables and bar charts
Marginal and joint frequencies for two-way tables
Conditional relative frequencies and accusations
Comparing distributions using bar charts
UNIT 2 – Sampling and Experimentation: Planning and conducting a study (10%-15%) Data must me collected
according to a well-developed plan if valid information on a conjecture is to be obtained. This plan includes classifying the
question and deciding upon a method of data collection and analysis
Overview of methods of data collection
Census
Sample survey
Experiment
Observational study
Planning and conducting surveys
Characteristics of a well-designed and well-conducted survey
Populations, samples, and random selection
Sources of bias in sampling and surveys
Sampling methods, including simple random sampling, stratified random sampling, and cluster sampling
Planning and Conducting Experiments
Characteristics of well-designed and well conducted experiments
Treatments, control groups, experimental units, random assignments, and replication
Sources of bias and confounding, including placebo effect and blinding
Completely randomized design
Randomized block design, including matched pairs
Generalizability of results and types of conclusions that can be drawn from observational studies, experiments,
and surveys
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ORANGE COUNTY HIGH SCHOOL OF THE ARTS
AP Statistics Course Outline
UNIT 3 – Anticipating Patterns: Exploring random phenomena using probability and simulation (20%-30%)
Probability is the tool used for anticipating what the distribution of data should look like under a given model.
Probability
Interpreting probability, including long-run relative frequency interpretation
“Law of Large Numbers” concept
Addition rule, multiplication rule, conditional probability, and independence
Discrete random variables and their probability distributions (binomial & geometric)
Simulation of random and probability distributions
Mean (expected value) and standard deviation of a random variable, and linear transformation of a
random variable
Combining Independent Random Variables
Notion of Independence vs. dependence
Mean and standard deviation for sums and differences of independent random variables
Normal Distribution
Properties of the normal distribution
Using tables of the normal distribution
The normal distribution as a model for measurements
Sampling Distributions
Sampling distributions of a proportion
Sampling distribution of a sample mean
Central limit theorem
Sampling distribution of a difference between two sample proportions
Sampling distribution of a difference between two independent sample means
Simulation of sampling distributions
t-distribution
chi-square distribution
UNIT 4 – Statistical Inference: Estimating population parameters and testing hypotheses (30%-40%) Statistical
inference guides the selection of appropriate models.
Estimation (point estimators and confidence intervals)
Estimating population parameters and margins of error
Properties of point estimators, including unbiasedness and variability
Logic of confidence intervals, meaning of confidence level and intervals, and properties of confidence
intervals
Large sample confidence interval for a proportion
Large sample confidence interval for a difference between two proportions
Confidence interval for a mean
Confidence interval for a difference between two means (unpaired and paired)
Confidence interval for the slope of a least-squares regression line
Tests of significance
 Logic of significance testing, null and alternate hypotheses; p-values; one and two-sided tests; concepts
of Type I and Type II errors; concept of power
 Large sample test for a proportion
 Large sample test for a difference between two proportions
 Test for a mean
 Test for a difference between two means (unpaired and paired)
 Chi-square test for goodness of fit, homogeneity of proportions, and independence (one and two-way
tables)
 Test for the slope of a least-squares regression line
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ORANGE COUNTY HIGH SCHOOL OF THE ARTS
AP Statistics Course Outline
Course – Curriculum Map
SEPTEMBER
Unit of Study/
Concept/Topic
OCTOBER
Unit of Study/
Concept/Topic
NOVEMBER
Unit of Study/
Concept/Topic
DECEMBER
Unit of Study/
Concept/Topic
JANUARY
Unit of Study/
Concept/Topic
Chapter 2 –
Data
Distributions
Chapter 4 –
Experimentation
Chapter 5 –
Probability
Continued
Chapter 6 –
Probability
Distributions
Chapter 7 –
Sampling
Distributions
AP Standards:
3.0,4.0
AP Standards:
1.0, 2.0, 9.0
AP Standards:
7.0, 8.0, 11.0,
15.0, 16.0
AP Standards:
7.0, 8.0, 11.0,
15.0, 17.0
FEBRUARY
Unit of Study/
Concept/Topic
MARCH
Unit of Study/
Concept/Topic
APRIL
Unit of Study/
Concept/Topic
MAY
Unit of Study/
Concept/Topic
JUNE
Unit of Study/
Concept/Topic
Chapter 8 –
Inference for
proportions
Chapter 9 –
Inference for
distributions
Chapter 11 –
Inference for
Regresison
Final Case
Study Project –
Upon
completion of
Video 26
UNIT 1 TEST
Chapter 3 –
Data
Relationships
Chapter 5 –
Probability
AP Standards:
4.0, 5.0, 6.0, 7.0,
8.0, 10.0,
12.0,13.0, 14.0
STAR TESTING
Chapter 10 –
Chi2
Distributions
UNIT 2 TEST
UNIT 3 TEST
AP Test
AP Standards:
7.0, 8.0, 11.0,
15.0, 16.0, 17.0
AP Standards:
7.0, 8.0, 11.0,
12.0,13.0
AP Standards:
14.0, 15.0, 16.0,
17.0
Page 4 of 4
AP Standards:
14.0, 15.0, 16.0,
17.0, 19.0
FINAL
Benchmark
Assessment
(Ch 1-9, 10, 12)
AP Standards:
14.0, 15.0, 16.0,
17.0, 19.0