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Statistics · AP · Sampling Distributions

What this topic is

In Statistics · AP, this CED topic focuses on: The Central Limit Theorem. In plain terms, students should be able to explain the main idea in their own words and complete a straightforward practice item with justification.

This topic is assessed on the AP Exam.

Why it matters

  • This topic trains the precise “approaches” language AP graders look for on limit items.
  • Sampling distributions connect probability models to inference about parameters.
  • Students must distinguish population parameters from sample statistics.
  • Shape, center, and spread of a sampling distribution drive later confidence intervals and tests.
  • Conditions (random, independence/10%, Normal/Large Counts) start here and never leave.

How you can support

  • Ask whether left- and right-hand behavior agree before concluding a two-sided limit.
  • Ask: “Are we talking about one sample result or the pattern of many samples?”
  • Have them name the parameter (p or μ) vs the statistic (p̂ or x̄).
  • Praise stating conditions before using a Normal model.
  • Ask what happens to spread when sample size increases.
  • Use a quick sketch of a sampling distribution and mark a sample result on it.

What not to do

  • Do not equate a limit with a function value when the graph has a hole or jump.
  • Do not confuse the distribution of sample data with the sampling distribution of a statistic.
  • Do not skip Large Counts / Normality conditions.
  • Do not forget the independence/10% condition when sampling without replacement.
  • Do not treat one sample’s histogram as the sampling distribution.

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