Calculat.dev LogoCalculat.dev - All Calculators, One Place.devAll Calculators, One Place.
Probability CalculatorsPopular Tool Runs Locally

Normal Distribution Calculator

Calculate probabilities and percentiles for standard and general normal distributions, z-scores, and interval areas.

Calculated Probability
34.1345%
z₁ score: 0.000 • z₂ score: 1.000
🎓

Did this calculation save you time?

Student Project

Hi! I'm a student developer building Calculat in my spare time. I was tired of searching for basic math tools and having to click through 10 spammy popups, loan ads, and cookie trackers.

I keep this website 100% free, private, and ad-free. If this helped you with your homework, project, or finances today, bookmarking this page or telling a friend helps me keep building more free tools!

Press ⌘ + D to Bookmark
Suggest What I Build Next

What Is a Normal Distribution Calculator?

The Normal (Gaussian) Distribution is the quintessential continuous probability distribution in statistics. Symmetrical and bell-shaped, it arises naturally in measurement errors, physical traits (height, blood pressure), standardized test scores (SAT, IQ), and financial market returns.

How to Use This Calculator

  1. Enter the population Mean (μ) and Standard Deviation (σ).
  2. Select your calculation region: Left-tailed P(X ≤ x₁), Right-tailed P(X ≥ x₁), Between P(x₁ ≤ X ≤ x₂), or Outside tails.
  3. Enter the target values (x₁ and x₂).
  4. Review the calculated probability percentage, bell curve area, and corresponding z-scores.

Normal Probability Density and CDF

f(x) = \frac{1}{\sigma \sqrt{2\pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}, \quad z = \frac{x-\mu}{\sigma}, \quad \Phi(z) = \frac{1}{2}\left[1 + \text{erf}\left(\frac{z}{\sqrt{2}}\right)\right]

Where μ is the mean, σ is the standard deviation, z is the standardized score, and erf is the Gauss error function.

Worked Example

Scenario: IQ scores follow a normal distribution with mean μ = 100 and standard deviation σ = 15. Find the probability of a person scoring between 100 and 115.

Calculate z1 for x1 = 100: z1 = (100 - 100) / 15 = 0.00 → Φ(0) = 0.5000.

Calculate z2 for x2 = 115: z2 = (115 - 100) / 15 = +1.00 → Φ(1) ≈ 0.8413.

Subtract CDF values: P(100 ≤ X ≤ 115) = 0.8413 - 0.5000 = 0.3413 (34.13%).

Result: 34.13% of the population scores between 100 and 115 IQ.

Tips & Key Notes

  • The Empirical Rule (68–95–99.7 rule): roughly 68.27% of data falls within 1σ of the mean, 95.45% within 2σ, and 99.73% within 3σ.
  • A z-score measures how many standard deviations an observation lies above or below the mean.

Frequently Asked Questions

What is a z-score?

A z-score (standard score) indicates how many standard deviations an element is from the mean: z = (x - μ) / σ. A positive z-score is above average; a negative is below.

What is the standard normal distribution?

The standard normal distribution is the special case of the normal distribution with mean μ = 0 and standard deviation σ = 1.

What percentage of data is beyond 2 standard deviations?

Approximately 4.55% of total data lies outside ±2 standard deviations (2.28% in each tail).

Why does the Central Limit Theorem make the normal distribution so important?

The Central Limit Theorem proves that the sum or average of a large number of independent random variables tends toward a normal distribution, regardless of the shape of the underlying population distribution.

Related Calculators

Explore similar tools