BETADIST Function (LibreOffice Calc)

• Computes the cumulative beta distribution
• Supports optional lower/upper bounds
• Useful for Bayesian inference, A/B testing, and bounded probability modeling
• Models variables constrained to a range (e.g., 0–1 or custom bounds)

Standard form (0 to 1)

BETADIST(x; alpha; beta)

Bounded form (a to b)

BETADIST(x; alpha; beta; a; b)

Arguments

• x:
  The value at which to evaluate the distribution.

• alpha:
  Shape parameter α (must be > 0).

• beta:
  Shape parameter β (must be > 0).

• a (optional):
  Lower bound of the interval (default = 0).

• b (optional):
  Upper bound of the interval (default = 1).

Standard beta CDF

=BETADIST(0.5; 2; 5)
→ cumulative probability at x = 0.5

Bounded beta distribution

=BETADIST(7; 2; 3; 0; 10)

Using cell references

=BETADIST(A1; B1; C1)

Bayesian posterior probability (Beta prior)

=BETADIST(0.8; Successes+1; Failures+1)

A/B test probability that p ≤ threshold

=BETADIST(0.6; A_success+1; A_fail+1)

Reliability modeling (bounded variable)

=BETADIST(A1; 3; 4; 10; 20)

Compute probability between two points

=BETADIST(x2; α; β) - BETADIST(x1; α; β)

Normalize x for bounded beta

=BETADIST((A1 - a) / (b - a); α; β)

Use with BETA.INV for quantile calculations

=BETAINV(0.95; α; β)

BETADIST returns a numeric probability between 0 and 1

Accepts:

• x within [a, b]
• α > 0
• β > 0

Behavior details

• If x < a → returns 0
• If x > b → returns 1
• α and β control skewness and shape
• Default bounds are 0 and 1
• Distribution is continuous and smooth

Invalid input → Err:502

BETADIST of an error → error propagates

• Use BETADIST for Bayesian posteriors and bounded probabilities
• Validate α and β to avoid domain errors
• Use bounded form for real-world ranges
• Combine with BETAINV for quantile analysis
• Use differences of BETADIST for interval probabilities

• Use BETAINV for inverse cumulative beta
• Use BETA for the probability density function
• Use NORMDIST, FDIST, and GAMMADIST for other distributions
• Use GAMMALN for stable parameter calculations

By mastering BETADIST, you can build powerful statistical, Bayesian, and probability‑driven models in LibreOffice Calc.