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Inference from sample statistics and margin of error

Review the key idea behind Inference from sample statistics and margin of error, then practice SAT-style questions until the pattern feels automatic.
SAT Math 11 practice questions Theory, examples & strategy
Inference from sample statistics and margin of error
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What this SAT skill is testing

Inference from a sample means using sample results to estimate something about a larger population. SAT questions focus on proportions, sample size, representative sampling, and margin of error.

A sample statistic is an estimate, not an exact population value. The margin of error describes a reasonable range around that estimate.

Key ideas

  • A sample proportion is ( rac{ ext{number with the trait}}{ ext{sample size}}).
  • An estimated population count is (( ext{sample proportion})( ext{population size})).
  • An estimate of (p%) with margin of error (m) percentage points gives the interval from (p-m) to (p+m).
  • Larger random samples usually produce smaller margins of error.
  • A larger sample does not fix a biased selection method.

Worked SAT-style example

In a random sample of 400 voters, 52% support a proposal. The margin of error is 4 percentage points.

The plausible interval is (52%-4%=48%) to (52%+4%=56%). A claim that exactly 52% of all voters support the proposal is too strong. A claim that population support could reasonably be 50% is consistent with the interval.

Estimating a population count

If 18% of a representative sample has a certain response and the population contains 2,500 people, the estimated count is (0.18(2500)=450). Because this is an estimate, the wording should not imply that exactly 450 people have that response.

Step-by-step method

  1. Identify the population the question asks about.
  2. Confirm that the sample can reasonably represent that population.
  3. Convert the sample result to a proportion or percent.
  4. Apply the proportion to the population, or build the margin-of-error interval.
  5. Choose a conclusion whose certainty matches the data.

Common traps

  • Adding 4% of the estimate when the problem says 4 percentage points.
  • Using the population size as the denominator for a sample proportion.
  • Treating the endpoints of an interval as impossible cutoffs rather than plausible bounds.
  • Assuming a result from one city represents an entire country.
  • Thinking that doubling the sample automatically removes all bias.

How to practice efficiently

For each question, write one of three setups before calculating: sample proportion, population estimate, or estimate ± margin of error. Most SAT questions in this unit reduce to one of those patterns.

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