Inverse Normal Distribution Calculator

Find x-values and z-scores from probabilities using the inverse normal function

Area Under the Curve

Must be between 0 and 1 (exclusive)

The probability p is the area to the left of x (left-tailed p-value).

Distribution Parameters

Average value of the distribution

Must be positive (σ > 0)

x-value & Z-score

x-value
0.0000
Critical value for P(X < x) = 0.5
Z-score
0.0000
Standard deviations from mean

Distribution: X ~ N(0, 1²)

Condition: P(X < x) = 0.5

Formula: x = μ + Z × σ = 0 + Z × 1

IQ Score Examples

Left-tailed Example

Question: What IQ score puts someone in the bottom 20% of the population?

Parameters: μ = 100, σ = 15, p = 0.20

Condition: P(X < x) = 0.20

Answer: x = 87.38 (Z-score = -0.8416)

Interpretation: 20% of people have IQ ≤ 87.38

Right-tailed Example

Question: What IQ score puts someone in the top 2.5%?

Parameters: μ = 100, σ = 15, p = 0.025

Condition: P(X > x) = 0.025

Answer: x = 129.4 (Z-score = 1.96)

Interpretation: 2.5% of people have IQ ≥ 129.4

Two-tailed Example

Question: What range contains the middle 80% of IQ scores?

Parameters: μ = 100, σ = 15, p = 0.80

Condition: P(|X - μ| < x) = 0.80

Answer: x₁ = 80.78, x₂ = 119.22

Interpretation: 80% of people have IQ between 80.78 and 119.22

Tail Area Types

Left-tailed

P(X < x) = p

Area to the left of x

Right-tailed

P(X > x) = p

Area to the right of x

Two-tailed

P(|X - μ| > x) = p

Area in both tails

Central Area

P(|X - μ| < x) = p

Area around the mean

Quick Tips

Probability must be between 0 and 1

Standard deviation must be positive

Z-score = (x - μ) / σ

Use μ=0, σ=1 for standard normal

Two-tailed splits probability equally

Understanding Inverse Normal Distribution

What is Inverse Normal Distribution?

The inverse normal distribution (invnorm) function calculates the x-value from a given probability p, mean μ, and standard deviation σ. It works backward from the area under the normal curve to find the critical value corresponding to that area.

Key Applications

  • Finding percentiles and quartiles
  • Determining critical values for hypothesis testing
  • Calculating confidence interval boundaries
  • Quality control and process capability analysis

Mathematical Foundation

If F(x) = p, then F⁻¹(p) = x

x = μ + Z × σ

  • F⁻¹(p): Inverse cumulative distribution function
  • p: Probability (area under curve)
  • x: Critical value we're solving for
  • μ: Mean of the distribution
  • σ: Standard deviation
  • Z: Standard normal quantile

Remember: Normal distribution calculates probability from x-values, while inverse normal calculates x-values from probabilities.

Normal vs. Inverse Normal

Normal Distribution

  • • Input: x-value
  • • Output: Probability (area)
  • • Question: "What's the probability?"
  • • Use: P(X < x) = ?

Inverse Normal

  • • Input: Probability (area)
  • • Output: x-value
  • • Question: "What's the critical value?"
  • • Use: P(X < ?) = p