MEDev.AI
0
Knowledge Center
Standards
Regulations
Tools
AI Tools
Analysis
Professional Development
Future Generations
Contact Us
--:--:-- --
--- --, ----
Session
0s
MEDev.AI
0
Knowledge Center
Standards
Regulations
Tools
AI Tools
Analysis
Professional Development
Future Generations
Contact Us
--:--:-- --
--- --, ----
Session
0s
MEDev.AI
0
Knowledge Center
Standards
Regulations
Tools
AI Tools
Analysis
Professional Development
Future Generations
Contact Us
--:--:-- --
--- --, ----
Session
0s
Back to Tools

Statistical Distributions in Medical Devices

Understanding probability distributions is essential for validation planning, reliability prediction, and statistical process control. Different distributions model different types of failure modes and biological processes.

  • Normal: Physiological measurements, manufacturing tolerances
  • Exponential: Random failures, constant failure rate
  • Weibull: Device lifetime, wear-out failures
  • Gamma: Multi-stage processes, biological reactions
Read Complete GuideDownload Tables (PDF)

Statistical Distribution Calculator

Visualize and analyze common probability distributions

Parameters

0200
150

Distribution Statistics

Mean

100.00

Median

100.00

Mode

100.00

Variance

225.00

Std Dev

15.00

Probability Density Function (PDF)

Cumulative Distribution Function (CDF)

Medical Device Applications

• Performance Testing: Most physiological measurements (blood pressure, glucose levels)

• Manufacturing Tolerances: Component dimensions and assembly variations

• Sample Size Calculation: Validation studies with normally distributed outcomes

Which Distribution Should I Use?

1Normal Distribution

Use when:

  • Data is symmetric around the mean
  • Natural variation in measurements
  • Many small independent factors contribute

Medical Device Examples:

  • Blood pressure measurements in a population
  • Manufacturing tolerance of component dimensions
  • Measurement error in calibrated devices
  • Sample size calculations for validation studies

2Exponential Distribution

Use when:

  • Time between random events
  • Memoryless process (constant failure rate)
  • Modeling early-life reliability

Medical Device Examples:

  • Time to first component failure
  • Electronic component reliability
  • Random sensor drift events
  • Calculating MTBF for non-repairable devices

3Weibull Distribution

Use when:

  • Modeling device lifetime
  • Failure rate changes over time
  • Shape parameter k describes failure pattern

Medical Device Examples:

  • Implantable device lifetime (wear-out, k '>' 1)
  • Battery degradation over time
  • Mechanical component fatigue failures
  • FDA-required reliability predictions

4Gamma Distribution

Use when:

  • Sum of multiple exponential events
  • Waiting time for multiple events
  • Modeling multi-stage processes

Medical Device Examples:

  • Time to biochemical reaction completion
  • Multi-component system failures
  • Service life of complex systems
  • Healthcare process queue modeling

Common Statistical Tests for Medical Devices

Normality Tests

Verify data follows normal distribution:

  • Shapiro-Wilk test (n < 50)
  • Kolmogorov-Smirnov test (n ≥ 50)
  • Q-Q plot visual inspection

Distribution Fitting

Determine best-fit distribution:

  • Maximum Likelihood Estimation (MLE)
  • Anderson-Darling goodness-of-fit
  • Chi-squared test for categorical data

Confidence Intervals

Estimate parameter uncertainty:

  • 95% CI for mean: x̄ ± 1.96(σ/√n)
  • Bootstrap methods for non-normal data
  • Likelihood ratio intervals for Weibull

Hypothesis Testing

Compare groups or validate specifications:

  • t-test for comparing means
  • F-test for comparing variances
  • Log-rank test for survival data

Regulatory Requirements

FDA Guidance - Statistical Software

FDA requires validation of statistical software used for regulatory submissions. Document assumptions about data distributions in validation protocols.

ISO 14971 - Risk Analysis

Probability estimates (occurrence ratings) should be based on statistical analysis where possible, not just engineering judgment. Distribution fitting provides objective evidence.

IEC 60601-1 - Reliability

Electrical medical device standard requires reliability analysis. Weibull analysis is commonly used to demonstrate compliance with reliability requirements.

Related Tools

Sample Size Calculator

Determine required sample sizes based on distribution assumptions

FMEA Calculator

Use distribution analysis to estimate occurrence ratings

Reliability Analysis

Apply Weibull analysis for lifetime predictions (Coming Soon)