AP Statistics 2.12 Sampling Distributions and the Central Limit Theorem Questions

Practise modelling sampling and randomization distributions, interpreting their centre and tails, and using sample size, standard error, and the CLT to explain shape.

Syllabus
Effective Fall 2026
Course
AP Statistics

Exam points

  • describe a theoretical sampling distribution from the statistic calculated over all fixed-size samples
  • generate an approximate sampling or randomization distribution through repeated resampling or reassignment
  • relate the simulated centre and tail area to a null model or an observed statistic
  • use the central limit theorem and standard error to describe normality and sample-size effects

Question 1

[Maximum number: 4]

Emma is moving to a large city and is investigating typical monthly rental prices of available one-bedroom apartments. She obtained a random sample of rental prices for 50 one-bedroom apartments taken from a Web site where people voluntarily list available apartments.

The distribution of the 50 rental prices of the available apartments is shown in the following histogram.

Figure for Question 1 — AP Statistics

Because Emma does not have the resources to develop the theoretical sampling distribution, she estimates the sampling distribution of the sample median using a process called bootstrapping. In the bootstrapping process, a computer program performs the following steps.

- Take a random sample, with replacement, of size 50 from the original sample.

- Calculate and record the median of the sample.

- Repeat the process to obtain a total of 15,000 medians.

Emma ran the bootstrap process, and the following frequency table is the bootstrap distribution showing her results of generating 15,000 medians.

Table for Question 1 — AP Statistics

The bootstrap distribution provides an approximation of the sampling distribution of the sample median. A confidence interval for the median can be constructed using a percentage of the values in the middle of the bootstrap distribution.

Question (a)

(a)

Instead of using the sample median as the point estimate for the population median, Emma wants to use an interval estimate. However, computing an interval estimate requires knowing the sampling distribution of the sample median for samples of size 50. Emma has one point, her sample median, in that sampling distribution. Using information about rental prices that are available on the Web site, describe how someone could develop a theoretical sampling distribution of the sample median for samples of size 50.

Question (b)

(b)

Find the percentage of bootstrap medians in the table that are equal to or between the values found in part (d).

Question (c)

(c)

Use your values from parts (d) and (e) to construct and interpret a confidence interval for the median rental price.

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