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AP Stats · Unit 6 Progress Check

AP Statistics Unit 6 Progress Check Inference for Categorical Data: Proportions walkthrough.

AP Statistics Unit 6 is inference for proportions, and the Unit 6 Progress Check MCQ tests whether you can pick the right z-procedure, check its conditions, and interpret the result in the wording the rubric wants. This walkthrough covers the question types and the traps. Explanations only — we never publish AP Classroom answer keys.

Updated August 2026Written by Mahmudul HasanFree · No signup

What Unit 6 covers

Unit 6 is Inference for Categorical Data: Proportions. Inference for proportions is roughly 12–15% of the AP Statistics exam and the first inference unit in the course.

Sampling distribution of a proportion
Centre at p, spread √(p(1−p)/n), approximately Normal when Large Counts is met.
One-sample z-interval
Estimating a population proportion with a confidence interval.
One-sample z-test
Testing a claim about a proportion against a null value.
Two-proportion procedures
Comparing proportions from two independent groups.
Conditions
Random, independent (the 10% condition), and Large Counts — checked every time.
Errors and power
Type I and Type II errors, and what raises the power of a test.

The Progress Check MCQ: what each question type tests

These are the question patterns that recur on this Progress Check, and what each one is really asking.

Interval or test?
“Estimate” signals an interval; “is there evidence that” signals a significance test.
Condition checking
Large Counts uses np and n(1−p). For a test, use the null value of p, not the sample proportion.
Interpret the interval
It gives plausible values for the population proportion — not for individuals or for the sample.
P-value interpretation
The probability of a result at least this extreme assuming the null is true.
Type I vs Type II
Type I rejects a true null; Type II fails to reject a false one. Describe both in context.

The Progress Check FRQ

Unit 6 free response follows the standard four-step structure: state the parameter and hypotheses, name the procedure, check the conditions, then calculate and conclude in context. The conclusion must link the P-value to the significance level and answer the original question in words.

Where students lose the most points

Using p-hat in the test standard error
A significance test uses the null value of p in the standard error; a confidence interval uses p-hat.
Skipping the conditions
They carry their own points and are not optional.
Saying “we accept the null”
You either reject it or fail to reject it.
Interpreting the interval as being about data
It is about the population parameter, not about individual observations.
Forgetting context in the conclusion
A conclusion without the setting and the parameter loses the final point.

How to work through this unit

Write the four steps as headings before computing anything — parameter, procedure, conditions, conclusion. The rubric is literally built on those four, so the structure earns points on its own.

Once you have finished the Progress Check, put your raw score into our AP Statistics Calculator to see roughly where that pace puts you on the 1–5 scale, and use the AP Statistics Review for the full exam format and study plan.

Frequently asked questions

Quick answers — written by humans, not a chatbot.

What does the AP Statistics Unit 6 Progress Check cover?

Inference for proportions: the sampling distribution of a sample proportion, one-sample z-intervals and z-tests, two-proportion procedures, the required conditions, and Type I and Type II errors.

Do I use p or p-hat in the standard error?

Use the null value of p when running a significance test, and use p-hat when constructing a confidence interval. Mixing these up is the most common Unit 6 error.

What is a Type I error?

Rejecting a null hypothesis that is actually true. A Type II error is failing to reject a null hypothesis that is actually false.

Do you post AP Statistics Unit 6 answer keys?

No. AP Classroom work is graded as your own, so we publish walkthroughs of the reasoning instead.

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