Weibull Survival and Lifetime Percentile Calculator
Evaluate a two-parameter Weibull survival model and find a chosen failure percentile from entered shape and scale.
YOUR CALCULATION
Result
β
Calculation steps
Work through one step at a time or reveal the complete calculation. The steps use your current inputs.
How to calculate
Evaluate the cumulative hazard and its exponential survival. Invert cumulative failure probability to find a requested percentile; plot the entered model without fitting data.
R(t)=exp[β(t/scale)^shape]; F(t)=1βR(t); tp=scale[βln(1βp)]^(1/shape)
Worked example
Shape 2 and scale 1000 h give survival exp(β1)β36.7879% at 1000 h and median 1000βln2β832.5546 h.
Assumptions and input details
Two-parameter zero-location lifetime model with positive shape 0.1β100 and positive scale. All times use the same user-chosen time unit; the hazard is per that unit. Parameters are supplied, not estimated or validated against failure observations. This is a model probability, not a product warranty or a forecast established from data. At time zero the hazard is unbounded for shape below one, explicitly shown as text.
References: NIST: Weibull lifetime model
Using this calculator
Can I enter my own problem?
Yes. Replace the example values with your own inputs. The result, calculation steps, tables and applicable diagrams update from those inputs. Blank or invalid values clear the result; example values are never silently substituted for missing inputs.
Are the results exact?
Results use floating-point arithmetic and displayed rounding. Read the formula, assumptions and any stated data precision before interpreting the result.
Is my input uploaded?
The calculation runs in your browser. No account, file upload or external AI service is required. Inputs are not saved between page reloads.
Apply an entered constant growth or decay rate to an initial quantity. Compare periodic and continuous models, view a time curve and find doubling time or half-life.
Combine component survival probabilities for an all-required series system or an at-least-one-required parallel system.
Compare an entered process mean and standard deviation with two specification limits and estimate normal-model tail proportions.
Reserved advertising space.