table of contents

Format of the New ExamWhen is the exam and how do I take it?How do I prepare for the exam?What resources does this study plan use?PRE-WORK: SET-UP YOUR STUDY ENVIRONMENT👆 UNIT 1: Exploring One-Variable DataBig takeaways:Definitely do this:If you have more time or want to dig deeper:✌️ UNIT 2: Exploring Two-Variable DataBig takeaways:Looking for Resources?If you have more time or want to dig deeper:🔎 UNIT 3: Collecting DataBig takeaways:Looking for Resources?🎲 UNIT 4: Probability & Random VariablesBig takeaways:Looking for Resources?If you have more time or want to dig deeper:📊 UNIT 5: Sampling DistributionsBig takeaways:Looking for Resources?If you have more time or want to dig deeper:⚖️ UNIT 6: Inference for Categorical Data (Proportions)Big takeaways:Looking for Resources?If you have more time or want to dig deeper:😼 UNIT 7: Inference for Quantitative Data (Means)Big takeaways:Looking for Resources?If you have more time or want to dig deeper:

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published on august 5, 2020

Last updated on August 4, 2020

👋🏼** Hi, I'm Jerry Kosoff from Atlanta, GA! **I'm an AP Stats teacher and streamer at Fiveable. This year's exam is different than we expected, but I'm here to help. I've put together this study guide to help keep you on track while you are studying from home. You can follow this guide on your own with a free Fiveable account! I'll also be joining a group of students live on Mondays @ 9pm ET during cram sessions. Pick up your cram pass to join us.

This year, the AP Statistics exam will look different than you were expecting. As we’re all on quarantine 😷 due to COVID-19, the College Board has decided to update the format and content of the test to fit an online testing format.

You’ll have 45-minutes to take the exam online and it will only cover units 1-7. If you have already studied content from unit 8 or 9, don’t stress! It’s all worth knowing.

**These units are on the exam.** **Click the unit to see the study guide! **(new unit guides coming soon!)

1 - 👆 Exploring One-Variable Data 2 - ✌️ Exploring Two-Variable Data 3 - 🔎 Collecting Data 4 - 🎲 Probability & Random Variables 5 - 📊 Sampling Distributions 6 - ⚖️ Inference for Categorical Data - Proportions 7 - 😼 Inference for Quantitative Data - Means

**Not on the exam:**

8 - ✳️ Inference for Categorical Data - Chi-Square

9 - 📈 Inference for Quantitative Data - Slopes

**What will be on the test?**

**Q1**- multi-focused FRQ- 25 minutes, worth 55% of your score
- May cover 2 or more units

**Q2**- multi-focused FRQ- 15 minutes, worth 45% of your score
- May cover 2 or more units

**Other info:**- There will not be an Investigative Task
- You should print or keep open the AP Statistics Formula Sheet
- Calculators are allowed, but not required.

**May 22 @ 2p Eastern! **Wherever you are in the world, this is the time you’ll take the test. Unless you have been approved for the make-up date in June, but only your school can request that. You’ll take the test online. There will be a practice simulation posted by College Board within the next few weeks.

With so many school closures and the stress of a global pandemic, this review season will be different than usual. If this is your first AP exam, welcome! Don’t worry, it’s not usually this chaotic.

We’ve put together this plan for you to follow between now and May. This will cover all of the units and leave you time to practice questions before test day. Some classes may have done units out of chronological order throughout the year, which is ok. The units don’t have to be taught in order. If you are learning new material on your own and need some help, use the chat bubble on http://fiveable.me. We’ll answer any questions you may have.

All of the required resources are free, including the AP stats cheat sheet. **You’ll need to ****create a free Fiveable account**** to jump in.** We’ve also linked a few other websites, articles, and YouTube videos that you can access for free. Some of the suggested resources include paid products. There are some documentaries that you can find on streaming sites with a paid membership and we’ll also list streams and practice questions that require a paid cram pass on Fiveable.

Before we begin, take some time to get organized. Remote learning can be great, but it also means you’ll need to hold yourself accountable more than usual.

**🖥 Create a study space.**

Make sure you have a designated place at home to study. Somewhere you can keep all of your materials, where you can focus on learning, and where you are comfortable. Spend some time prepping the space with everything you need and you can even let others in the family know that this is your study space. Claim your territory by printing out and posting your AP stats cheat sheet PDFs! We at Fiveable don't love that term, but our creators have lovingly crafted these 1 page cram charts.

**📚 Organize your study materials.**

Get your notebook, textbook, prep books, or whatever other physical materials you have. Also create a space for you to keep track of review. Start a new section in your notebook to take notes or start a Google Doc to keep track of your notes. Get your self set up!

**📅 Plan designated times for studying.**

The hardest part about studying from home is sticking to a routine. Decide on one hour every day that you can dedicate to studying. This can be any time of the day, whatever works best for you. Set a timer on your phone for that time and really try to stick to it. The routine will help you stay on track.

**🏆 Decide on an accountability plan.**

How will you hold yourself accountable to this study plan? You may or may not have a teacher or rules set up to help you stay on track, so you need to set some for yourself. First set your goal. This could be studying for x number of hours or getting through a unit. Then, create a reward for yourself. If you reach your goal, then x. This will help stay focused!

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 1 is about creating and analyzing graphs of data. This includes both categorical and quantitative data. For categorical data, we should be able to read and create tables and bar graphs, and calculate proportions/percentages. For quantitative data, we should be able to read and create dotplots, stemplots, histograms, and boxplots. We should also be able to describe the shape, center, variability (spread), and any unusual features of a distribution of quantitative data. This includes making calculations such as mean, median, range, interquartile range (IQR), and standard deviation. Our descriptions and calculations can be used to compare data from multiple groups. Finally, Unit 1 ends with describing the position of individuals within a quantitative data set, including using percentiles and z-scores. This leads us to an initial exploration of the Normal Distribution, though we will study that more in-depth in Units 4-5.

🎥

**Watch these videos from the Fiveable archives:**- Analyzing Categorical Variables: An intro to some key terms and graphs (use first 15 minutes)
- Graphing & Analyzing Quantitative Variables: The types of graphs you need to know!
- Describing Data in a Distribution: A breakdown of percentile a cumulative graphs
- Normal Distributions: A good intro to all things Normal!

📰

**Check out these articles:**- Relative Dominance: A real-life example of how z-scores can help compare individuals from different distributions, using golfers (source: Grantland)

✍️

**Practice**:- Practice an AP-Style Problem: check out this post and practice your free-response skills!

💎 Check out some online applets:

- Mean vs. Median interactive applet: Play with this applet to get a sense of how changing different data values impacts the mean and median
- Normal Distribution applet: A visual of the Standard Normal Curve. Update the mean and standard deviation to look at any data set.

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 2 is about creating and analyzing graphs of data when two variables are measured about each individual in a data set. For categorical data, we should be able to read and create two-way tables or segmented bar graphs, and calculate conditional percentages. These can be used to comment on the association (or lack thereof) between the two variables. For quantitative data, we should be able to read, create, and describe scatterplots, which can also be used to comment on apparent association between two variables.

The second half of Unit 2 is then focused on linear regression, a process by which we can make predictions about one quantitative variable (a response variable) using another (an explanatory variable). We should be able to use Least-Squares Regression Lines to make these predictions, and interpret several components of the LSRLs (including slope, intercept, and other calculated values such as s or r2)

**🎥 Watch these videos from the Fiveable archives:**- Analyzing Categorical Variables: Start at 14:38 for an example of two-way tables and stay for segmented bar graphs
- Describing Scatterplots & Association: How to describe the direction, strength, and form of an association, as well as an introduction to the correlation coefficient
*r* - Using Least-Squares Regression Lines: How to make predictions from regression lines and calculating residuals
- Advanced Linear Regression: Interpreting “s”, “r2”, and reading computer outputs of regression data

✍️

**Practice**:- Practice an AP-Style Problem: check out this post and practice your free-response skills!

🌶 Join the live cram stream for unit 2. Get your cram pass now.

💎 Check out some online applets:

- Least-Squares Regression: Try to guess the least-squares regression line from a scatterplot of data

😀 Just for fun!

- Spurious Correlations: Data sets with very high “r” values that… well… you’ll see... [Source: Tyler Vigen]

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

While Units 1-2 were about graphing and analyzing sets of data, Unit 3 is about examining the methods through which we can collect that data. For sample surveys, we should be able to describe various methods of selecting samples, particularly the random methods (simple random, stratified random, cluster, and systematic samples). However, not all samples are collected through a random process, and we should be prepared to discuss possible sources of bias in surveys (including via non-random selection processes).

We then turn to the differences between observational studies and experiments, and the features of a well-designed experiment. We should be able to define many common terms associated with experiments (many of which you’ve likely seen in other courses!), and compare and contrast several common experimental designs: completely randomized design, randomized block design, and matched-pairs design.

**🎥 Watch these videos from the Fiveable archives:**- Sampling Methods and Sources of Bias: A breakdown of the different ways we can take samples, and how to talk about bias on the AP exam.
- Experiments and Observational Studies: All things experiments! Includes a discussion of the possible pitfalls of observational studies (confounding)

✍️

**Practice**:- AP-Style Problem #1: a practice question on surveys and sampling methods.
- AP-Style Problem #2: a practice question on observational studies/experiments

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 4 is where AP Statistics gets “math-y,” with lots of calculations and formulas. We are asked to calculate or interpret probabilities in a variety of settings, beginning with the understanding that probability reflects what we should expect to occur over the long run. We should be able to design and execute simulations for a given scenario - and then the calculations begin. We should be able to calculate the probability of multiple events using a variety of strategies (including Two-Way Tables, Tree Diagrams, and/or Venn Diagrams).

We should also be able to categorize different events as “mutually exclusive” or “independent,” with justification. Conditional probability [P(A | B)] plays a big role in this part of the unit. Shifting over to random variables, we should be able to calculate the mean (expected value) or standard deviation of a random variable, and combine them using similar rules to Unit 1. We conclude Unit 4 with a look at Binomial and Geometric random variables, which are two special types of variables that arise frequently in applications.

🎥

**Watch these videos from the Fiveable archives:**- Randomness & Simulation: Explore some definitions (and myths) about probability and randomness
- Basic Probability Rules: A breakdown of commonly-tested probability rules, using Two-Way Tables for most scenarios
- Random Variables & Binomial/Geometric Distributions: A summary of Random Variable facts & formulas

📰

**Check out these articles:**- Statistics in Court: Incorrect Probabilities: An exploration of the misuse of probability rules in court cases [source: Significance Magazine]

**✍️ Practice:**- Practice FRQ #1: Some basic probability calculations using a discrete random variable
- Practice FRQ #2: Test your knowledge of binomial scenarios and simulations
- Practice FRQ #3: A scenario involving a two-way table

💎

**Check out some online applets:**- Dice & The Law of Large Numbers: Play with this applet to get a sense of how probability works over the “long run”
- Coin Flips: A similar applet using coin flips

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 5 provides the bridge from descriptive statistics (Units 1-4) to inferential statistics (Units 6-9). After reviewing the Normal Distribution and introducing the idea of using sample statistics (like p or x) to estimate population parameters (like p or ), we explore the creation of sampling distributions.

We meet the conditions for inference: **random** samples, **large** samples (for categorical variables, we need at least 10 expected successes and failures; for quantitative variables, we need n to be at least 30), and **independent** observations (which turns into the “10% rule” for sampling without replacement: if the sample size n is less than 10% of the population size N, we can do calculations as if we sampled with replacement).

If these conditions are met, the sampling distribution we build will be approximately Normal and all of our formulas for calculating mean and standard deviation of sampling distributions on the formula sheet will hold. We then build sampling distributions for sample proportions/sample means and the difference of sample proportions/sample means.

**🎥 Watch these videos from the Fiveable archives:**- Sampling Distributions for Proportions: an intro to vocabulary surrounding sampling distributions, and a simulation using a virtual “candy machine”
- Sampling Distributions for Means: an intro to the building of a sampling distribution for x-bar and a summary of the Central Limit Theorem

**✍️ Practice:**- Unit 5 Practice FRQ: describe a sampling distribution and compute an associated probability

💎

**Check out some online applets:**- The "Candy Machine": Build a sampling distribution for p-hat.
- Sampling Distribution for x-bar: See the Central Limit Theorem in action! Definitely try to make a “custom” graph to give the population a unique shape.

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 6 is where we meet Confidence Intervals and Hypothesis Tests for the first time, specifically z-intervals and z-tests for population proportions. After learning “the basics” about confidence intervals (what’s a confidence level? What’s a margin of error?), we construct and interpret 1 and 2-sample z-intervals.

These intervals, built from samples, can be used to justify claims about a population. Then, after exploring the rationale behind hypothesis tests (including how to write null/alternative hypotheses and interpret a p-value in context), we run 1 and 2-sample z-tests. Finally, we meet “Errors”: both Type I (rejecting a true H0) and Type II (failing to reject a false H0), and define the “Power” of a test as the probability of correctly rejecting a false H0. This unit is often heavily tested and is well worth your time to review!

**🎥 Watch these videos from the Fiveable archives:**- Confidence intervals for p: An intro to Confidence Intervals and a breakdown of how to construct and interpret 1-sample z-intervals.
- Hypothesis Tests for p: An intro to Hypothesis Tests and practice running 1 and 2-sample z-tests.
- Errors & Power of a Test: A breakdown of the types of errors in hypothesis testing, and how to increase the power of a test.

**📰 Check out these articles:**- Understanding Type I and Type II Errors: A breakdown of the Types of Errors with “boy who cried wolf” examples [Source: William Schmarzo]

**✍️ Practice:**- Unit 6 Practice FRQ #1: Test your knowledge about Confidence Intervals!
- Unit 6 Practice FRQ #2: “Convincing Statistical Evidence that…”

💎

**Check out some online applets:**- Confidence Intervals for p: play with the population parameters and see what we mean by “confidence level”
- Reasoning of a Hypothesis Test: demonstrates the idea of Hypothesis Testing using basketball free-throws.

🌶 Join the live cram stream with Jerry Kossoff. Get your cram pass now.

Unit 7 is an extension of Unit 6: we basically do everything again, but with t-procedures instead of z-procedures! We build Confidence Intervals and run Hypothesis Tests for a population mean or a difference of population means.

For the difference of population means, we must be able to distinguish between if we are running a 2-sample procedure or a matched-pairs procedure (in which we will use a 1-sample procedure to execute the process).

🎥

**Watch these videos from the Fiveable archives:**- Confidence Intervals for Mu: An refresher on Confidence Intervals and a breakdown of the t-distribution
- Hypothesis Tests for Mu: Lots of good FRQ practice
- Errors & Power of a Test: A breakdown of the types of errors in hypothesis testing, and how to increase the power of a test. (same as from Unit 6)
- Review of z and t procedures: A (mostly) comprehensive review of Units 6 and 7. Great for last-minute preparations!

✍️

**Practice**:- Unit 7 Practice FRQ #1: should we shut down the production line?
- Unit 7 Practice FRQ #2: which type of test should we run?

💎

**Check out some online applets:**- Confidence Intervals for Mu: play with the population parameters and see what we mean by “confidence level”
- Statistical Power: Explore how “Power” of a test is impacted by various inputs

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