Calculate Interval Probability Between Two Bounds

Enter mean (μ), standard deviation (σ), lower bound (a), and upper bound (b).

Mean $\mu$ (e.g. 100).
Standard deviation $\sigma$ (e.g. 15).
Lower bound $a$ (e.g. 85).
Upper bound $b$ (e.g. 115).

Calculation Results

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Mathematical Standard--

Calculated using normal distribution cumulative interval integration: P(a < X < b) = \Phi\left(\frac{b - \mu}{\sigma}\right) - \Phi\left(\frac{a - \mu}{\sigma}\right)

*Note: Interval probability represents the area under the normal bell curve between lower bound a and upper bound b.

Quick Summary

The Normal Distribution Probability Calculator evaluates the probability $P(a < X < b)$ that a random variable falls between lower bound $a$ and upper bound $b$.

Formula Explanation

P(a < X < b) = P(X < b) - P(X < a) = \Phi(Z_b) - \Phi(Z_a)
Z_a = \frac{a - \mu}{\sigma}, \quad Z_b = \frac{b - \mu}{\sigma}

How It Works

To find the probability between two limits $a$ and $b$, convert both limits into Z-scores ($Z_a$ and $Z_b$) and subtract cumulative left-tail area $\Phi(Z_a)$ from $\Phi(Z_b)$. The Normal Distribution Probability Calculator computes exact bell curve interval probabilities instantly.

Step-by-Step Worked Example

Practical Problem: For an IQ distribution with mean $\mu = 100$ and SD $\sigma = 15$, find the probability of scoring between $a = 85$ and $b = 115$.

  1. Step 1: Calculate lower Z-score ($Z_a$): $Z_a = (85 - 100) / 15 = -15 / 15 = \mathbf{-1.0000}$.
  2. Step 2: Calculate upper Z-score ($Z_b$): $Z_b = (115 - 100) / 15 = +15 / 15 = \mathbf{+1.0000}$.
  3. Step 3: Look up cumulative areas: $\Phi(-1.00) = 0.1587$; $\Phi(+1.00) = 0.8413$.
  4. Step 4: Subtract cumulative probabilities: $P(85 < X < 115) = 0.8413 - 0.1587 = \mathbf{0.6826\text{ (68.26\%)}}.$
  5. Step 5: Interpretation: 68.26% of the population scores between 85 and 115 on the IQ test ($\pm 1\sigma$).

Real-World Calculation Examples

Scenario 1: IQ Score Between 85 & 115 (±1σ)

Parameters: a = 85, b = 115, μ = 100, σ = 15
Result: P(85 < X < 115) = 0.6827 (68.27% of population).

Scenario 2: IQ Score Between 70 & 130 (±2σ)

Parameters: a = 70, b = 130, μ = 100, σ = 15
Result: P(70 < X < 130) = 0.9545 (95.45% of population).

Scenario 3: Factory Parts Within Spec (495mm to 505mm)

Parameters: a = 495, b = 505, μ = 500, σ = 2.5
Result: 95.45% Yield.

Scenario 4: Exam Scores Between 70 & 85

Parameters: a = 70, b = 85, μ = 75, σ = 8
Result: P(70 < X < 85) = 0.6284.

Key Benefits of Using This Calculator

Dual Bound Integration ($a$ to $b$)

Calculates exact area probability under the bell curve between any lower bound $a$ and upper bound $b$.

Lower & Upper Z-Score Output

Displays $Z_a$ and $Z_b$ standardized scores simultaneously.

Tail Probability Breakdown

Outputs lower tail $P(X < a)$ and upper tail $P(X > b)$ areas.

100% Free & Client-Side

Executes locally in your browser with zero latency or web server transmission.

Frequently Asked Questions (FAQ)

How do I calculate normal distribution probability between two numbers?

Calculate Z-scores for both numbers ($Z_a$ and $Z_b$) and subtract cumulative left-tail area $\Phi(Z_a)$ from $\Phi(Z_b)$.

What is 68-95-99.7 Empirical Rule for normal intervals?

$\mu \pm 1\sigma \rightarrow 68.27\%$, $\mu \pm 2\sigma \rightarrow 95.45\%$, and $\mu \pm 3\sigma \rightarrow 99.73\%$.

How do I calculate normal interval probability in Excel?

Use formula =NORM.DIST(b, mean, sd, TRUE) - NORM.DIST(a, mean, sd, TRUE).

What if lower bound a is negative infinity?

If $a = -\infty$, the interval probability equals the left cumulative probability $P(X < b)$.

What if upper bound b is positive infinity?

If $b = +\infty$, the interval probability equals the right tail probability $P(X > a)$.

Can normal interval probability be negative?

No — since $b > a$, $\Phi(Z_b) \ge \Phi(Z_a)$, so probability is always between $0.0$ and $1.0$.

What is tolerance interval in quality engineering?

A tolerance interval calculates bounds $[a, b]$ expected to contain a specified proportion (e.g. 99%) of future production units.

How are normal interval probabilities used in finance (VaR)?

Value at Risk (VaR) calculates the maximum expected financial loss within a specified confidence interval.

What is central 90% normal interval boundary?

Central 90% area falls between $Z = -1.645$ and $Z = +1.645$ ($\mu \pm 1.645\sigma$).

What is central 95% normal interval boundary?

Central 95% area falls between $Z = -1.96$ and $Z = +1.96$ ($\mu \pm 1.96\sigma$).