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For observations k,k+2,k+4, find variance using denominator 3 as specified.

Read the idea, work independently, then explain what changed.

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高一必修 第二册(A版).pdf · 9.2 · PDF 200 / printed page 193

Revisit first: Random sampling

TOPIC 01

Estimating a population from a sample

Build understanding of estimating a population from a sample through definitions, contrasting cases and justified applications.

What you will be able to explain

  • Use estimating a population from a sample to state a justified conclusion.
  • Connect representations and justify the steps, including boundary cases.
  • Explain a solution and apply the idea to a changed situation.

Try it. Leave your reasoning visible.

Use one hint at a time. A correction explains what changed, not just the final answer.

01 / Standard#Your turn

For observations k,k+2,k+4, find variance using denominator 3 as specified.

k=3k=3
  • Use the domain, units and sampling assumptions stated in the question.
Skills and prerequisite lessons

Working and explanation

BUILD THE REASONING

Hint 1
Translate counts into sample proportions and keep classes, units and uncertainty visible.
Hint 2
Center the data before squaring; use the stated denominator.
Worked solution
  1. Translate counts into sample proportions and keep classes, units and uncertainty visible.

  2. Calculate or simplify this relation.

    v=[(−2)2+02+22]/3=8/3v=[(-2)^2+0^2+2^2]/3=8/3
  3. This descriptive variance differs from an unbiased sample variance using n−1.

The requested value is 2.66666667.

Checks and common pitfalls: This descriptive variance differs from an unbiased sample variance using n−1.

Think first. Reveal a hint when the class is ready.

Focus on one question

Teacher preparation and assessment

Question sequence

  • What must be true before using the main rule for estimating a population from a sample?
  • Which representation makes this task easier, and why?
  • Change one assumption. Does the conclusion survive?

Board plan

  • Use estimating a population from a sample to state a justified conclusion.
  • Distribution estimates: Use frequency, class density and sample proportions to describe data.
  • Location and spread: Mean, median, quantiles and variance answer different questions about the distribution.
  • Close with: conditions → representation → reasoning → check.

Anticipated thinking

  • Expected reasoning: Use frequency, class density and sample proportions to describe data.
  • Expected reasoning: Mean, median, quantiles and variance answer different questions about the distribution.
  • Expected correction: A sample estimate is not a known exact population parameter.

Assessment checklist

  • 1: identify the givens and required quantity.
  • 1: choose a valid definition, representation or method.
  • 1: present connected, correct reasoning.
  • 1: check conditions and explain the result.

No sign-in. Work stays in this browser. Export before clearing browser data. Written reasoning is assessed with a checklist.

Curriculum and source notes ↗