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Overview

Probability questions often reduce to counting. Define a clear sample space, count favorable outcomes, and use complements when easier.

When outcomes are not equally likely, use conditional probability, tree diagrams, or symmetry to compute probabilities directly.

Key Ideas

  • For equally likely outcomes, use P(A)=P(A) = favorable outcomes / total outcomes.
  • P(Ac)=1P(A)P(A^c) = 1 - P(A) is often simpler to compute.
  • Use the rule of product to count outcomes in multi-step experiments.
  • Conditional probability: P(AB)=P(AB)/P(B)P(A\mid B) = P(A\cap B)/P(B).
  • Independence: P(AB)=P(A)P(B)P(A\cap B) = P(A)P(B).

Core Skills

Define the Sample Space

List the outcomes or count them with a method like the rule of product. Every probability is a ratio of favorable to total outcomes.

Use Complements Early

If the event is "at least" or "not equal", count the opposite event first.

Track Conditional Events

After a condition occurs, update the sample space before counting.

Expected value

For a random variable XX with outcomes x1,x2,,xnx_1, x_2, \ldots, x_n occurring with probabilities p1,p2,,pnp_1, p_2, \ldots, p_n is the weighted average:

E[X]  =  i=1nxipi.E[X] \;=\; \sum_{i=1}^{n} x_i \, p_i.

The single most important property is the linearity of expectation, for any random variables XX and YY (even dependent ones),

E[X+Y]  =  E[X]+E[Y].E[X + Y] \;=\; E[X] + E[Y].

Worked Example

Two fair dice are rolled. What is the probability the sum is 77?

There are 3636 equally likely outcomes. The favorable pairs are (1,6),(2,5),(3,4),(4,3),(5,2),(6,1)(1,6),(2,5),(3,4),(4,3),(5,2),(6,1), so the probability is 6/36=1/66/36 = 1/6.

More Examples

Example 1: Conditional Probability

A bag has 3 red and 2 blue marbles. Two marbles are drawn without replacement. What is the probability the second marble is red given the first is red?

After drawing one red, the bag has 2 red and 2 blue left, so the probability is 2/4=1/22/4 = 1/2.

Example 2: Independence Check

Flip a fair coin twice. Let AA be "first flip is heads" and BB be "second flip is heads". Then P(A)=P(B)=1/2P(A)=P(B)=1/2 and P(AB)=1/4=P(A)P(B)P(A\cap B)=1/4 = P(A)P(B), so AA and BB are independent.

Example 3: Complement

What is the probability that at least one of two fair dice shows a 66?

Complement: no 66 on either die. That is (5/6)2=25/36(5/6)^2 = 25/36. So the probability is 125/36=11/361 - 25/36 = 11/36.

Example 4: Expected Value

A fair die is rolled once. If it shows kk, you win k2k^2 dollars. What is the expected winnings?

1+4+9+16+25+366=916\frac{1+4+9+16+25+36}{6} = \frac{91}{6}

Strategy Checklist

  • Decide if outcomes are equally likely.
  • Use complements for "at least" or "not" statements.
  • Rebuild the sample space after conditioning.
  • Check independence before multiplying probabilities.

Common Pitfalls

  • Assuming outcomes are equally likely without checking.
  • Forgetting to count order when it matters.
  • Using P(AB)=P(A)/P(B)P(A\mid B) = P(A) / P(B) by mistake.
  • Treating dependent events as independent.

Practice Problems

StatusSourceProblem NameDifficultyTags
AJHSMEEasy
Show TagsCounting, Probability
AJHSMEEasy
Show TagsIndependent Events, Probability
AJHSMENormal
Show TagsCombinatorics, Parity
AJHSMENormal
Show TagsParity, Probability, Spinners
AJHSMEEasy
Show TagsProportions, Ratios
AJHSMENormal
Show TagsIndependent Events, Parity
AJHSMENormal
Show TagsCounting Outcomes, Dice
AJHSMENormal
Show TagsIndependent Events, Parity
AJHSMENormal
Show TagsDice, Probability
AJHSMENormal
Show TagsArea, Geometric Probability
AJHSMEVery Easy
Show TagsPermutations, Probability
AJHSMENormal
Show TagsCounting, Dice, Product
AJHSMENormal
Show TagsComparison, Probability, Sample Space
AMC 8Very Easy
Show TagsComplementary Counting, Probability
AMC 8Normal
Show TagsCoin Flipping, Independent Events
AMC 8Easy
Show TagsDice, Multiples
AMC 8Very Easy
Show TagsComplementary Probability, Fractions
AMC 8Normal
Show TagsBinomial Probability, Coin Flips
AMC 8Normal
Show TagsDivisibility, Probability, Product
AMC 8Easy
Show TagsIndependent Events, Parity
AMC 8Easy
Show TagsRatios, Variables
AMC 8Normal
Show TagsIndependent Events, Parity
AMC 8Normal
Show TagsCombinatorics, Favorable Outcomes
AMC 8Normal
Show TagsCombinatorics, Divisibility Rules
AMC 8Hard
Show TagsGeometric Probability, Parity
AMC 8Normal
Show TagsCombinatorics, Geometry
AMC 8Normal
Show TagsCasework, Number Theory, Perfect Squares
AMC 8Easy
Show TagsArea, Counting
AMC 8Easy
Show TagsPrime Numbers, Probability
AMC 8Easy
Show TagsDivisibility Rules, Permutations
AMC 8Easy
Show TagsCombinatorics, Seating Arrangements
AMC 8Easy
Show TagsCounting, Dice
AMC 8Very Easy
Show TagsCoin Toss, Counting Outcomes
AMC 8Easy
Show TagsCasework, Independent Events
AMC 8Easy
Show TagsPermutations
AMC 8Easy
Show TagsBinomial Probability, Expected Value
AMC 8Very Easy
Show TagsIndependent Events, Parity
AMC 8Easy
Show TagsCombinatorics, Independent Events
AMC 8Easy
Show TagsCombinations, Zero Product Property
AMC 8Normal
Show TagsCombinations, Conditional Probability
AMC 8Easy
Show TagsCombinatorics, Dependent Events
AMC 8Hard
Show TagsCounting, Parity, Permutations
AMC 8Easy
Show TagsAdjacency, Combinatorics
AMC 8Hard
Show TagsCombinatorics, Geometry Probability
AMC 8Easy
Show TagsCounting, Symmetry
AMC 8Normal
Show TagsConditional Probability, Set Theory
AMC 8Easy
Show TagsIndependent Events, Parity
AMC 8Easy
Show TagsAlgebraic Setup, Ratios
AMC 8Easy
Show TagsIndependent Events, Perfect Squares
AMC 8Hard
Show TagsExpected Value, Markov Chains, States
AMC 8Hard
Show TagsGrid, Inclusion-Exclusion
AMC 8Hard
Show TagsCombinatorics, Probability, Seating Arrangements

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