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Binomial Distribution

Apply the binomial distribution to count successes in fixed trials with conditions BINS.

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🎯 Binomial Distribution

BINS Conditions

Random variable XX ~ Binomial(n,p)(n, p) if:

  • Binary: Each trial has two outcomes (success/failure)
  • Independent: Trials independent
  • Number: Fixed number nn of trials
  • Same: Probability pp same on every trial

Example: Draw 10 cards with replacement, count red cards. XX ~ Binomial(10, 0.5)

NOT binomial: Drawing without replacement (probabilities change)

Binomial Probability Formula

P(X=k)=(nk)pk(1−p)n−kP(X = k) = \binom{n}{k} p^k (1-p)^{n-k}

Where:

  • nn = number of trials
  • kk = number of successes (0 to nn)
  • pp = probability of success on each trial
  • (nk)=n!k!(n−k)!\binom{n}{k} = \frac{n!}{k!(n-k)!} = number of ways to choose kk from nn

Worked Example

Scenario: 80% of AP Stats students pass the exam. If 5 students take the exam, what's P(X=4)P(X = 4) students pass?

  • n=5n = 5, k=4k = 4, p=0.8p = 0.8, (1−p)=0.2(1-p) = 0.2

P(X=4)=(54)(0.8)4(0.2)1=5×0.4096×0.2=0.4096P(X = 4) = \binom{5}{4} (0.8)^4 (0.2)^1 = 5 × 0.4096 × 0.2 = 0.4096

Check: P(X=4)≈0.41P(X = 4) ≈ 0.41 or 41%

What's P(X≥4)=P(X=4)+P(X=5)P(X ≥ 4) = P(X=4) + P(X=5)?

P(X=5)=(55)(0.8)5(0.2)0=1×0.32768×1=0.32768P(X=5) = \binom{5}{5} (0.8)^5 (0.2)^0 = 1 × 0.32768 × 1 = 0.32768

P(X≥4)≈0.41+0.33≈0.74P(X ≥ 4) ≈ 0.41 + 0.33 ≈ 0.74

Mean and Standard Deviation

E(X)=μ=npE(X) = \mu = np

SD(X)=σ=np(1−p)\text{SD}(X) = \sigma = \sqrt{np(1-p)}

Example: 5 students, p=0.8p=0.8

  • E(X)=5(0.8)=4E(X) = 5(0.8) = 4 students
  • SD(X)=5(0.8)(0.2)=0.8≈0.894SD(X) = \sqrt{5(0.8)(0.2)} = \sqrt{0.8} ≈ 0.894

Normal Approximation to Binomial

If nn large enough (np≥10np ≥ 10 AND n(1−p)≥10n(1-p) ≥ 10), then:

X approximately N(np,np(1−p))X \text{ approximately } N(np, \sqrt{np(1-p)})

Use normal curve to approximate binomial probabilities (easier than formula!)

Continuity correction: For exact binomial, P(X=k)P(X=k) ≈ P(k−0.5<X<k+0.5)P(k-0.5 < X < k+0.5) using normal

Common Mistakes

  • Forgetting BINS conditions before applying binomial
  • Using (1−p)n−k(1-p)^{n-k} as (1−p)n(1-p)^n
  • Confusing P(X=k)P(X = k) with P(X≤k)P(X \leq k)
  • Sampling without replacement (violates independence)

Decision Rule

Two outcomes, fixed nn, independent trials, constant pp? → Binomial Need P(X=k)P(X = k)? → Use formula Need P(X≤k)P(X \leq k)? → Sum probabilities or use table/calculator

AP Exam Tip

Always state BINS conditions explicitly: "This is binomial because..." Common calculation: "P(X=k)P(X=k) means exactly kk successes"; "P(X≥k)P(X \geq k) means at least kk successes."

📚 Practice Problems

1Problem 1easy

❓ Question:

A quiz has 10 multiple choice questions, each with 4 choices. A student guesses randomly. What is the probability of exactly 3 correct answers?

💡 Show Solution

This is binomial with n=10, p=0.25 (one correct out of 4), k=3. P(X=3) = C(10,3) × (0.25)³ × (0.75)⁷ = 120 × 0.0156 × 0.1335 ≈ 0.250. About 25% chance of exactly 3 correct by random guessing on a 10-question quiz.

2Problem 2medium

❓ Question:

A vaccine is 85% effective. In a sample of 20 vaccinated individuals, find the probability that at least 18 are protected (X ≥ 18).

💡 Show Solution

Binomial with n=20, p=0.85. Find P(X≥18) = P(X=18) + P(X=19) + P(X=20). P(X=18) = C(20,18) × (0.85)¹⁸ × (0.15)² ≈ 190 × 0.0394 × 0.0225 ≈ 0.169. P(X=19) = C(20,19) × (0.85)¹⁹ × (0.15)¹ ≈ 20 × 0.0335 × 0.15 ≈ 0.100. P(X=20) = (0.85)²⁰ ≈ 0.0388. P(X≥18) ≈ 0.169 + 0.100 + 0.039 ≈ 0.308. About 31% chance that 18 or more are protected.

3Problem 3hard

❓ Question:

Manufacturing produces items with defect rate p=0.02. In a batch of 50, find the probability of at most 2 defects. Also calculate E(X) and SD(X).

💡 Show Solution

Binomial n=50, p=0.02. P(X≤2) = P(X=0) + P(X=1) + P(X=2). P(X=0) = C(50,0)(0.02)⁰(0.98)⁵⁰ ≈ 0.364. P(X=1) = C(50,1)(0.02)¹(0.98)⁴⁹ ≈ 50 × 0.02 × 0.371 ≈ 0.371. P(X=2) = C(50,2)(0.02)²(0.98)⁴⁸ ≈ 1225 × 0.0004 × 0.379 ≈ 0.186. P(X≤2) ≈ 0.921. E(X) = np = 50(0.02) = 1. SD(X) = √(np(1-p)) = √(50×0.02×0.98) ≈ 0.99. Over 92% probability of 2 or fewer defects; mean defects is 1 with SD ≈ 1.

Explain using:

⚠️ Common Mistakes: Binomial Distribution

Avoid these 3 frequent errors

📌 Related Topics in Unit 4: Probability, Random Variables, and Probability Distributions

❓ Frequently Asked Questions

What is Binomial Distribution?▾
Apply the binomial distribution to count successes in fixed trials with conditions BINS.
How can I study Binomial Distribution effectively?▾
Start by reading the study notes and working through the examples on this page. Then use the flashcards to test your recall. Practice with the 3 problems provided, checking solutions as you go. Regular review and active practice are key to retention.
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Binomial Distribution is part of the AP Statistics course on Study Mondo, specifically in the Unit 4: Probability, Random Variables, and Probability Distributions section. You can explore the full course for more related topics and practice resources.
Are there practice problems for Binomial Distribution?▾
Yes, this page includes 3 practice problems with detailed solutions. Each problem includes a step-by-step explanation to help you understand the approach.