Normal Distribution Calculator

Calculate probabilities, z-scores, and percentiles for normal distributions

Find probability for a given value
Center of the distribution
Spread of the distribution
Point of interest on the distribution

Bell Curve Visualization

Enter values to see the normal distribution curve

Understanding Normal Distribution

The normal distribution, also known as the Gaussian distribution or bell curve, is one of the most important probability distributions in statistics. It appears naturally in many real-world phenomena.

Key Concepts

  • Mean (μ): The center of the distribution, representing the average value.
  • Standard Deviation (σ): Measures how spread out values are from the mean. A larger σ means more spread.
  • Z-Score: The number of standard deviations a value is from the mean. Formula: z = (x - μ) / σ
  • Percentile: The percentage of values that fall below a given point.

The 68-95-99.7 Rule

  • ~68% of values fall within 1 standard deviation of the mean (μ ± σ)
  • ~95% of values fall within 2 standard deviations (μ ± 2σ)
  • ~99.7% of values fall within 3 standard deviations (μ ± 3σ)

Real-World Examples

IQ Scores

Mean = 100, SD = 15

IQ scores are designed to follow a normal distribution, making it easy to compare individual scores.

Heights

Adult heights in populations

Most people cluster around average height, with fewer very tall or very short individuals.

Test Scores

Standardized exams (SAT, GRE)

Large groups taking tests typically produce normally distributed scores.

Pro Tip: Try experimenting with different values! Set mean=100, SD=15, and try x-values of 85, 100, and 115 to see how they correspond to different percentiles.