Geometric Distribution Formula

The Formula

P(X = k) = (1 - p)^{k-1} \cdot p, \quad k = 1, 2, 3, \ldots

When to use: How many times do you have to roll a die before you get a 6? The geometric distribution answers this kind of question. Each trial is independent, and you keep going until you succeed. Most of the time it doesn't take too long, but occasionally you have an unlucky streak—that's why the distribution has a long right tail.

Quick Example

Probability of getting first heads on the 4th flip of a fair coin: P(X = 4) = (1 - 0.5)^{4-1} \cdot 0.5 = (0.5)^3 \cdot 0.5 = 0.0625

Notation

X \sim \text{Geom}(p). Mean: E(X) = \frac{1}{p}. Standard deviation: \sigma = \frac{\sqrt{1-p}}{p}.

What This Formula Means

The probability distribution for the number of independent Bernoulli trials needed to get the first success, where each trial has success probability p.

How many times do you have to roll a die before you get a 6? The geometric distribution answers this kind of question. Each trial is independent, and you keep going until you succeed. Most of the time it doesn't take too long, but occasionally you have an unlucky streak—that's why the distribution has a long right tail.

Formal View

P(X = k) = (1-p)^{k-1} p for k = 1, 2, 3, \ldots; E(X) = \frac{1}{p}, \text{Var}(X) = \frac{1-p}{p^2}

Worked Examples

Example 1

medium
A basketball player makes free throws with probability p=0.7. Find the probability they make their first free throw on exactly the 3rd attempt.

Solution

  1. 1
    Geometric distribution: P(X=k) = (1-p)^{k-1} \cdot p
  2. 2
    Here: first make on attempt k=3; p=0.7; q=1-p=0.3
  3. 3
    P(X=3) = (0.3)^{3-1} \times 0.7 = (0.3)^2 \times 0.7 = 0.09 \times 0.7 = 0.063
  4. 4
    Interpretation: 6.3% chance the first success comes on the 3rd attempt (2 misses then a make)

Answer

P(X=3) = (0.3)^2(0.7) = 0.063. 6.3% chance first make is on attempt 3.
The geometric distribution models the number of trials until the first success. The formula requires k-1 failures (each with probability q=1-p) followed by one success (probability p). It assumes independence between trials.

Example 2

hard
For a geometric distribution with p=0.4: (a) find P(X \leq 3), (b) find the expected number of trials until first success.

Common Mistakes

  • Using the binomial formula when the number of trials is not fixed—if you're counting trials until the first success, use geometric.
  • Forgetting the memoryless property: 'I've failed 10 times, so I'm due for a success' is the gambler's fallacy.
  • Mixing up the two conventions: P(X = k) = (1-p)^{k-1}p (trials until first success, k \geq 1) vs P(Y = k) = (1-p)^k p (failures before first success, k \geq 0).

Why This Formula Matters

Models real situations like number of sales calls until a sale, number of attempts until passing an exam, or how many parts you inspect before finding a defective one.

Frequently Asked Questions

What is the Geometric Distribution formula?

The probability distribution for the number of independent Bernoulli trials needed to get the first success, where each trial has success probability p.

How do you use the Geometric Distribution formula?

How many times do you have to roll a die before you get a 6? The geometric distribution answers this kind of question. Each trial is independent, and you keep going until you succeed. Most of the time it doesn't take too long, but occasionally you have an unlucky streak—that's why the distribution has a long right tail.

What do the symbols mean in the Geometric Distribution formula?

X \sim \text{Geom}(p). Mean: E(X) = \frac{1}{p}. Standard deviation: \sigma = \frac{\sqrt{1-p}}{p}.

Why is the Geometric Distribution formula important in Math?

Models real situations like number of sales calls until a sale, number of attempts until passing an exam, or how many parts you inspect before finding a defective one.

What do students get wrong about Geometric Distribution?

Students confuse geometric (trials until FIRST success) with binomial (number of successes in FIXED trials). Also watch out: some textbooks define X as the number of failures before the first success, shifting the formula.

What should I learn before the Geometric Distribution formula?

Before studying the Geometric Distribution formula, you should understand: binomial distribution, independent events, expected value.