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A game pays t with probability 1/4 and 0 otherwise; entry fee is 2. Find expected net gain.

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高三選擇性必修 第三册(A版).pdf · 7.3 · PDF 67 / printed page 62

Revisit first: Discrete random variables and distributions

TOPIC 01

Numerical characteristics of random variables

Compute expectation and variance and distinguish transformation from random independence.

What you will be able to explain

  • Compute expectation and variance and distinguish transformation from random independence.
  • Justify the method and check the conditions in a new situation.

Try it. Leave your reasoning visible.

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

01 / Transfer#Your turn

A game pays t with probability 1/4 and 0 otherwise; entry fee is 2. Find expected net gain.

t=14t=14
  • Variance is nonnegative; variance of a sum includes covariance unless independence is justified.
Skills and prerequisite lessons

Working and explanation

BUILD THE REASONING

Hint 1
List the possible values and probabilities before computing moments.
Hint 2
Net gain=payment-2.
Worked solution
  1. List the possible values and probabilities before computing moments.

  2. Apply the stated relation and retain its conditions.

    E(G)=14/4−2=1.5E(G)=14/4-2=1.5
  3. Expected net gain differs from the gross expected payment and is not a guaranteed outcome.

The requested value is 1.5.

Checks and common pitfalls: Expected net gain differs from the gross expected payment and is not a guaranteed outcome.

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

Focus on one question

Teacher preparation and assessment

Question sequence

  • Compute expectation and variance and distinguish transformation from random independence.
  • Which condition is essential in numerical characteristics of random variables?
  • Does doubling all outcomes double or quadruple the variance?

Board plan

  • Defining relation: Compute expectation and variance and distinguish transformation from random independence.
    E(X)=∑xpx;Var⁡(X)=E(X2)−[E(X)]2E(X)=\sum xp_x;\quad\operatorname{Var}(X)=E(X^2)-[E(X)]^2
  • Conditions: Variance is nonnegative; variance of a sum includes covariance unless independence is justified.

Anticipated thinking

  • E(X²) is generally not [E(X)]².

Assessment checklist

  • 1 mark: choose the correct representation and conditions.
  • 1 mark: establish the intermediate relation.
  • 1 mark: complete a connected calculation or proof.
  • 1 mark: interpret and check the conclusion.

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

Curriculum and source notes ↗