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nCr = n! / (r! × (n-r)!)

Probability Calculator

Calculate combinations, permutations, binomial probability, and more with step-by-step solutions. Perfect for GCSE and A-Level students.

C

Combinations (nCr)

Order doesn't matter

nCr counts selections where order doesn't matter (e.g., choosing a committee)

Key Formulas

Factorial

n! = n × (n-1) × ... × 2 × 1

5! = 5 × 4 × 3 × 2 × 1 = 120

Permutations

nPr = n! / (n-r)!

5P2 = 5!/(5-2)! = 120/6 = 20

Combinations

nCr = n! / (r! × (n-r)!)

5C2 = 5!/(2! × 3!) = 120/12 = 10

Basic Probability

P(E) = Favorable / Total

P(Ace) = 4/52 = 1/13

Addition Rule

P(A∪B) = P(A) + P(B) - P(A∩B)

P(A∪B) = 0.3 + 0.4 - 0.1 = 0.6

Conditional

P(A|B) = P(A∩B) / P(B)

P(A|B) = 0.12 / 0.4 = 0.3

Common Mistakes

Confusing nPr with nCr

nPr is for arrangements (order matters), nCr is for selections (order does not matter). nPr is always ≥ nCr.

Forgetting 0! = 1

By definition, 0! = 1, not 0. This is needed for formulas like nC0 = 1.

Adding P(A∩B) instead of subtracting

In P(A∪B) = P(A) + P(B) - P(A∩B), we subtract P(A∩B) because it is counted twice.

Using addition for independent events

For independent events, P(A∩B) = P(A) × P(B), not P(A) + P(B).

Confusing P(A|B) with P(B|A)

P(A|B) ≠ P(B|A) unless A and B have special relationships. Always check what is given.

Probability > 1 or < 0

All probabilities must be between 0 and 1. If you get a value outside this range, check your calculation.

Understanding Probability & Combinatorics

What is Probability?

Probability measures how likely an event is to occur, expressed as a number between 0 (impossible) and 1 (certain).

Key formula:

P(Event) = Favorable outcomes / Total outcomes

Example: P(rolling 6) = 1/6

Permutations vs Combinations

  • nPr:Order MATTERS (arrangements)
  • nCr:Order does NOT matter (selections)
  • nPr is always ≥ nCr
  • nCr = nPr ÷ r!

Worked Examples

Example 1: Combinations (nCr)

How many ways can you choose 3 people from a group of 10 for a committee?

Step 1: Identify: n = 10, r = 3

Step 2: Formula: 10C3 = 10! / (3! × 7!)

Step 3: Calculate: 3,628,800 / (6 × 5,040)

Result: 10C3 = 120 ways

Example 2: Permutations (nPr)

How many ways can 8 runners finish 1st, 2nd, and 3rd place?

Step 1: Identify: n = 8, r = 3

Step 2: Formula: 8P3 = 8! / (8-3)! = 8! / 5!

Step 3: Simplify: 8 × 7 × 6 = 336

Result: 8P3 = 336 arrangements

Example 3: Binomial Probability

What is the probability of getting exactly 3 heads in 5 coin flips?

Step 1: n = 5, k = 3, p = 0.5

Step 2: P(X=3) = 5C3 × 0.5³ × 0.5²

Step 3: = 10 × 0.125 × 0.25

Result: P(X=3) = 0.3125 = 31.25%

Example 4: Conditional Probability

If P(A∩B) = 0.15 and P(B) = 0.5, what is P(A|B)?

Step 1: Formula: P(A|B) = P(A∩B) / P(B)

Step 2: Substitute: P(A|B) = 0.15 / 0.5

Result: P(A|B) = 0.3 = 30%

Exam Tips

🎯

Order Matters?

Ask yourself: does the order of selection matter? If yes → nPr. If no → nCr.

0️⃣

Remember 0! = 1

By definition, 0! = 1. This is essential for formulas like nC0 = 1 and nCn = 1.

Subtract for Union

P(A∪B) = P(A) + P(B) - P(A∩B). Subtract to avoid double-counting!

✖️

Multiply for Independent

For independent events: P(A∩B) = P(A) × P(B). Don't add them!

📊

Check Probability Range

All probabilities must be between 0 and 1. If you get a value outside, check your work!

🔄

Complement Trick

P(at least one) = 1 - P(none). Often easier than calculating directly!

Frequently Asked Questions

What is the difference between permutations and combinations?

Permutations (nPr) count arrangements where ORDER MATTERS - like choosing 1st, 2nd, and 3rd place winners. Combinations (nCr) count selections where ORDER DOES NOT MATTER - like choosing a committee of 3 people. The formula nPr = n!/(n-r)! and nCr = n!/(r!(n-r)!).

How do I know when to use nPr vs nCr?

Ask yourself: "Does the order matter?" If you're arranging things in specific positions (like race placements, seating arrangements, or passwords), use nPr. If you're just selecting a group (like a committee, lottery numbers, or a hand of cards), use nCr.

What is conditional probability P(A|B)?

Conditional probability P(A|B) is the probability of event A occurring given that event B has already occurred. The formula is P(A|B) = P(A∩B) / P(B). For example, the probability of drawing a King given that you drew a face card is P(King|Face) = P(King ∩ Face) / P(Face) = (4/52) / (12/52) = 4/12 = 1/3.

When do I use the binomial probability formula?

Use binomial probability when you have: (1) a fixed number of independent trials, (2) each trial has exactly two outcomes (success/failure), (3) the probability of success is constant for each trial, and (4) you want the probability of exactly k successes. Examples: coin flips, multiple choice guessing, defective products in a batch.

Why is 0! equal to 1?

0! = 1 by definition, and it makes mathematical formulas work correctly. For example, it ensures that nCn = n!/n!×0! = 1 (there's exactly one way to choose all items from a set) and nC0 = n!/0!×n! = 1 (there's exactly one way to choose nothing - do nothing).

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