AP STATISTICS
UNIT 3 REVIEW
CHAPTERS 11-13
M S . E H N A T 4 TH P E R I O D
MADDY MIDDLETON, ORA PARKER EDDY,
RACHEL BAILEY, BERKLEY LANE
OVERVIEW
Chapters 11-13 are overall about gathering
data. Chapter 11 is about understanding
randomness, how to do simulations, and how to
correctly produce random outcomes. Chapter 12
talks about sample surveys: what makes them up, the
different kinds, blocking, and bias. A lot of
vocabulary is introduced in chapter 12. Similar to
chapter 12, chapter 13 has many new vocabulary
words as well. Chapter 13 also addresses
observational studies vs. experimental studies, retro
and prospective studies, and how to correctly design
an experiment.
CHAPTER 11
• Simulations model a real-world situation by using
random-digit outcomes to mimic the uncertainty of
a response variable of interest.
• Trials are the sequence of several components
representing events that we are pretending will take
place.
• RANDOMNESS
- No one knows the outcome.
- Everything should be equally likely.
CHAPTER 11
• An example when using a calculator:
- Trying to get 5 different cereal toys in boxes of
cereal.
- In the calculator: RandInt(0, 5, 20)
- 0-5 represents the different cereal toys.
- 20 represents the number of boxes in each trial.
- For each trial, record how many #s it takes to get a
full set.
• Another:
- RandInt(1,6)
- Random number between 1-6 that represents a
simulation of rolling a dice.
CHAPTER 11
• Random number tables have also been created for
use during simulations.
- Without a calculator, count the amount of numbers
until receiving a full set of how many numbers
you’re looking for.
CHAPTER 12
• Population: All the individuals
• Sample: Smaller group of individuals selected from
population.
• Sample Surveys ask small groups of people (opinion)
questions that will hopefully represent the entire
population. Randomly selected people!!!
• Parameters: Numerically value of a model for
population
• Randomly selecting individuals creates an “on
average…” answer.
• BIAS!!! Not good to have when giving sample
surveys. Does not give true representation of
populations answers.
SAMPLING TECHNIQUE
I want to know if students cheat
on their AP Stats tests. So, I need
to conduct a survey! Which
technique is best?
SIMPLE RANDOM SAMPLE
• Assign number to all students taking AP Stats
• Randomly select 100 numbers and survey those
students
STRATIFIED RANDOM SAMPLE
• Sample two students from every AP Stats class.
Undercoverage or Overcoverage- inadequate
representation of a population
CLUSTER RANDOM SAMPLE
• Select a random school and survey every student
taking AP Stats at that school
Bias:
School selected could
excel in the AP Stats
arena or have very poor
performance
SYSTEMATIC SAMPLE
• Stand outside of 6 AP Stats classrooms and survey
every third student
• Bias: The first ones out of the room finished faster
and most likely cheated
CONVENIENCE SAMPLE
• Set up a table outside of testing room and ask
students to take the survey about cheating; IT IS
NOT MANDATORY!
• Bias: students who cheat are not going to admit to
cheating, especially if the survey is not anonymous
Please tell me if you
cheated!
CHAPTER 13
• Observational Study
• Researchers don’t assign choices; just observe
• Retrospective- identify subjects, then collect past
data
• Prospective- identify subjects in advance, and
collect data as they occur
• Shows trends and possible relationships
• Cannot prove cause and effect
CHAPTER 13
• Randomized - Comparative Experiments
• Proves cause and effect
• Must identify at least one explanatory variable, a
factor, to manipulate and a response variable to
measure
• An experiment:
-manipulates factor levels
-randomly assigns subjects to those treatments
-compares the responses of the subjects groups
across treatment levels
CHAPTER 13
• Experimental Design
• Control: make conditions as similar as possible for
treatment groups
• Randomization: allows us to equalize the effects of
unknown variation
• Replication: repeat the experiment
• Use diagrams to visually display experiment groups.
• Blocking(not required): used when groups of
experimental units are similar. The differences caused by
the treatments can be seen more clearly. Randomization
occurs within the blocks.
CHAPTER 13 VOCABULARY
• blinding: used to avoid bias
• placebo: fake treatment that looks like the
treatment being tested (essential for blinding)
• matching: reduces variability
• confounding : two factors are confounded when
the levels are associated with each other.
• anecdote: the outcome of an experiment on a
single subject
• lurking: a lurking variable is thought of as a variable
associated with both y and x that makes it appear
that x may be causing y.