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Probability: Rules, Conditional, Independence — HS Statistics practice questions

22 multiple-choice questions and 22 flashcards on Probability: Rules, Conditional, Independence, about 15% of the HS Statistics bank. Every one carries a written rationale.

Written and maintained by the CoStudy team · last updated 2026-10-02 · how we write and review questions

What this chapter covers

Probability: Rules, Conditional, Independence is one of 7 chapters in CoStudy's HS Statistics bank, and it holds 22 of the bank's 150 multiple-choice questions — roughly 15% of the total. That proportion is not arbitrary: chapters follow the certifying body's published exam outline, and the number of questions in each is set by that domain's published weight, so the share of your practice time this chapter takes matches the share of the real exam it accounts for.

Studying by chapter is worth doing once you have a diagnostic score. A single overall percentage tells you whether you are close; it does not tell you which domain is dragging. Working a weak chapter in isolation, and re-testing it in isolation, is the fastest way to move a score that has stalled — and it is why the mock exams in CoStudy report by domain rather than as one number.

Free Probability: Rules, Conditional, Independence practice questions

9 questions drawn from this chapter, with the full rationale shown — the controlling principle behind the right answer, and why each wrong option tempts and fails.

What is the expected value of one roll of a fair six-sided die?

  1. 3
  2. 6
  3. 3.5
  4. 21

Answer: C — 3.5

C) Correct — (1 + 2 + 3 + 4 + 5 + 6)/6 = 21/6. A) Rounds down; the expected value need not be a possible roll. B) Is the largest outcome. D) Adds the outcomes without dividing by 6.

How many 3-letter arrangements can be made from 5 different letters, with no repeats?

  1. 10
  2. 125
  3. 60
  4. 15

Answer: C — 60

C) Correct — Order matters: 5 · 4 · 3. A) Counts combinations, ignoring order. B) Allows letters to repeat. D) Multiplies 5 × 3.

P(A) = 0.5, P(B) = 0.4, and P(A and B) = 0.2. Find P(A or B).

  1. 0.9
  2. 0.2
  3. 0.7
  4. 0.5

Answer: C — 0.7

C) Correct — P(A) + P(B) − P(A and B) = 0.5 + 0.4 − 0.2. A) Forgets to subtract the overlap, counting it twice. B) Is P(A and B). D) Uses only P(A).

A fair coin lands heads 5 times in a row. What is P(heads) on the next flip?

  1. Less than 1/2, because tails is due
  2. More than 1/2, because heads is on a streak
  3. 1/2
  4. 1/64

Answer: C — 1/2

C) Correct — The flips are independent; the coin has no memory. A) The gambler's fallacy: past flips do not affect the next one. B) Streaks do not change a fair coin's probability. D) Is the probability of 6 heads in a row, not of the next flip.

Two dice are rolled. How many outcomes are in the sample space?

  1. 12
  2. 11
  3. 36
  4. 6

Answer: C — 36

C) Correct — 6 outcomes for the first die × 6 for the second. A) Adds 6 + 6. B) Counts the possible sums, 2 through 12. D) Counts one die.

Of 200 students, 80 play a sport, and 30 of those are seniors. What is P(senior | plays a sport)?

  1. 0.15
  2. 0.40
  3. 0.375
  4. 0.625

Answer: C — 0.375

C) Correct — 30 of the 80 athletes: 30/80. A) Is P(senior and plays a sport) = 30/200. B) Is P(plays a sport) = 80/200. D) Is the share of athletes who are not seniors.

A fair coin is flipped 3 times. What is P(at least one head)?

  1. 3/8
  2. 7/8
  3. 1/2
  4. 3/2

Answer: B — 7/8

B) Correct — 1 − P(no heads) = 1 − 1/8. A) Is P(exactly one head). C) Uses the probability for one flip. D) Adds 1/2 three times; probabilities cannot exceed 1.

P(rain) = 0.35. What is P(no rain)?

  1. 0.35
  2. 0.65
  3. 0.5
  4. 1.35

Answer: B — 0.65

B) Correct — Complement: 1 − 0.35. A) Copies the probability of rain. C) Assumes rain and no rain are equally likely. D) Adds 1 instead of subtracting from 1.

Events A and B are independent exactly when:

  1. P(A and B) = P(A)·P(B)
  2. P(A and B) = 0
  3. P(A) = P(B)
  4. P(A) + P(B) = 1

Answer: A — P(A and B) = P(A)·P(B)

A) Correct — Knowing one happened does not change the chance of the other. B) Defines mutually exclusive events. C) Equal probabilities say nothing about independence. D) Describes complements in some cases.

Probability: Rules, Conditional, Independence flashcards

4 cards from the 22 in this chapter.

Mutually exclusive (disjoint) events?

Can't both happen. P(A or B) = P(A) + P(B).

Sample space?

Set of all possible outcomes of a random experiment. P(sample space) = 1.

Bayes' theorem?

P(A|B) = P(B|A) × P(A) / P(B). Updates probability with new info.

Complement rule?

P(not A) = 1 - P(A).

Practise the full chapter

These are a sample. The full Probability: Rules, Conditional, Independence chapter runs 44 items with per-chapter progress tracking, on the web and in the iOS app.

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