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Overview of Units for AP Statistics
AP Statistics
Unit 1: Exploring data: Describing patterns and departures from patterns
Unit 2: Sampling and experimentation: Planning and conducting a study
Unit 3: Anticipating patterns: Exploring random phenomena using probability
and simulation
Unit 4: Statistical inference: Estimating population parameters and testing
hypotheses
Unit 1: Exploring data: Describing patterns and departures
from patterns
Goals:
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Constructing and interpreting graphical displays of
distributions of univariate data
Summarizing distributions of univariate data
Comparing distributions of univariate data
Exploring bivariate data
Exploring categorical data
find center and spread of data
recognize clusters and gaps
determine outliers and other unusual features
visualize shape of curves
measure center: median, mean
measure spread: range, interquartile range, standard
deviation
measure position: quartiles, percentiles, standardized
scores (z-scores)
gather information from boxplots
see the effect of changing units on summary measures
compare center and spread: within group, between
group variation
compare clusters and gaps
compare outliers and other unusual features
compare shapes
analyze patterns in scatterplots
calculate correlation and linearity
find the least squares regression line
graph residual plots, outliers, and influential points
use transformations to achieve linearity: logarithmic and
power transformations
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use frequency tables and bar charts
calculate marginal and joint frequencies for two-way tables
find conditional relative frequencies and association
compare distributions using bar chart
Vocabulary:
center, spread, clusters, gaps, outliers, shape, median,
mean, range, interquartile range, standard deviation, quartiles,
percentiles, z-scores, boxplots, units, measures, patterns,
scatterplots, correlation, linearity, squares regression line,
residual plots, logarithmic, power transformations, frequency
tables, bar charts, marginal frequencies, joint frequency, twoway tables, conditional relative frequency
Textbook:
Chapters 3 – 10
Tasks:
Unit 2: Sampling and experimentation: Planning and
conducting a study
Goals:
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Overview of methods of data collection
Planning and conducting surveys
Planning and conducting experiments
Generalizability of results and types of conclusions that can
be drawn from observational studies, experiments and
surveys
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determine the necessity of a census
conduct a sample survey
conduct an experiment
conduct an observational study
determine the characteristics of a well-designed and wellconducted survey
define populations, samples and random selection
find sources of bias in sampling and surveys
differentiate between sampling methods, including simple
random sampling, stratified random sampling and cluster
sampling
notice the characteristics of a well designed and wellconducted experiment
recognize treatments, control groups, experimental units,
random assignments and replication
find sources of bias and confounding, including placebo
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effect and blinding
conduct a completely randomized design
outline randomized block design, including matched-pairs
design
Vocabulary:
census, sample survey, experiment, observational study,
populations, samples, random sample, sources of bias,
simple random sampling, stratified random sampling, cluster
sampling, treatments, control groups, experimental units,
random assignments, replication, confounding, placebo
effect, blinding, randomized design, randomized block
design, match pairs design
Textbook:
Chapters 12-13
Tasks:
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Unit 3: Anticipating patterns: Exploring random phenomena
using probability and simulation
Goals:
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Explore probabilities
Combining independent random variables
The normal distribution
Sampling distributions
I can…
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interpret probability, including long-run relative
frequency interpretation
understand the “law of large numbers” concept
use the addition rule, multiplication rule, conditional
probability and independence
differentiate between discrete random variables and their
probability distributions, including binomial and geometric
conduct a simulation of random behavior and probability
distributions
calculate mean (expected value) and standard deviation of a
random variable, and linear transformation of a random
variable
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understand the notion of independence versus dependence
calculate mean and standard deviation for sums and
differences of independent random variables
determine the properties of normal distribution
use tables of the normal distribution
see the normal distribution as a model for measurements
use sampling distribution of a sample proportion
use sampling distribution of a sample mean
understand the central limit theorem
use sampling distribution of a difference between two
independent sample proportions
use sampling distribution of a difference between two
independent sample means
use simulation of sampling distributions
calculate a t-distribution
calculate a chi-square distribution
Vocabulary:
probability, long-run relative frequency interpretation,
law of large numbers, addition rule, multiplication rule,
conditional probability and independence, discrete random
variables, probability distributions, binomial, geometric,
random behavior, mean, standard deviation, random variable,
linear transformation, independence, dependence, sums,
independent random variables, normal distribution, tables,
model for measurement, sampling distribution, sample
proportion, sample mean, central limit theorem, independent
sample proportions, independent sample means,
t-distribution, chi-square distribution
Textbook:
Chapters 6, 11, 14-18, 22-24, 26
Tasks:
Unit 4: Statistical inference: Estimating population
parameters and testing hypotheses
Goals:
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Estimation with point estimators and confidence intervals
Tests of significance
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estimate population parameters and margins of error
use properties of point estimators, including unbiasedness
and variability
understand logic of confidence intervals, meaning of
confidence level and confidence intervals and properties of
confidence intervals
calculate large sample confidence interval for a proportion
calculate large sample confidence interval for a difference
between two proportions
calculate confidence interval for a mean
calculate confidence interval for a difference between two
means (unpaired and paired)
find the confidence interval for the slope of a least squares
regression line
use the steps of logic of significance testing, null and
alternative hypotheses;p-values; one- and two-sided tests;
concepts of Type 1 and Type II errors; concept of power
conduct a large sample test for a proportions
conduct a large sample test for a difference between two
proportions
test for a mean
test for a difference between two means (unpaired and paired)
use a chi-square test for goodness of fit, homogeneity or
proportions, and independence (one- and two-way tables)
test for the slope of a least squares regression line
Vocabulary:
estimate, population parameters, margins of error, point
estimators, unbiasedness, variability, logic of confidence
intervals, confidence level, confidence intervals, slope of
least squares regression line, significance testing, null and
alternative hypotheses, p-value, one- and two-sided test,
type I & II errors, concept of power,
Textbook:
Chapters 19-27
Tasks…