DOWN WITH BORING DATA

UNCERTAINTY
CALCULATOR

ISO/IEC GUIDE 98-3 (GUM) COMPLIANT

TOOL SPOTLIGHT

MEASUREMENT UNCERTAINTY CALCULATOR TRANSFORMS LABORATORY COMPLIANCE

Our ISO/IEC Guide 98-3 compliant uncertainty calculator transforms complex statistical analysis into intuitive, professional-grade tools. With interactive examples, real-time calculations, and comprehensive reporting features, it's changing how laboratories approach measurement uncertainty and quality control.

PUBLISHED: 10:00 AM, MAY 26, 2025 | BY LAB STATS TEAM
UNDERSTANDING UNCERTAINTY

What is Measurement Uncertainty?

Every measurement we make in the laboratory has some degree of uncertainty. Think of it like taking a photo - even with the best camera, there's always some blur or imperfection. Measurement uncertainty helps us understand and quantify these imperfections.

Type A Uncertainty: Random Variations

This comes from repeated measurements of the same thing. Like weighing the same sample multiple times - you'll notice small differences each time. The calculator uses statistical methods to determine how much these variations affect your final result.

Type B Uncertainty: Known System Effects

These are uncertainties we know about from other sources, such as:

  • Calibration certificates
  • Equipment specifications
  • Temperature effects
  • Reference material uncertainties
How to Use This Calculator:
  1. Type A Section: Enter your repeated measurements, one per line. The calculator will determine the uncertainty from these variations.
  2. Type B Section: Add each known source of uncertainty. For each source:
    • Normal distribution: Use for calibration certificates where ± is given (divide the ± value by 2)
    • Rectangular distribution: Use when only a range is known (like temperature effects: ±2°C)
    • Triangular distribution: Use when values near the center are more likely than the extremes
  3. Combined Uncertainty: The calculator combines both types and applies your chosen confidence level (k-factor):
    • k=1: 68% confidence
    • k=2: 95% confidence (most common for reporting)
    • k=3: 99.7% confidence
Quick Tips:
  • Always use at least 10 repeated measurements for Type A if possible
  • Don't forget environmental factors in Type B (temperature, humidity, etc.)
  • Most accreditation bodies expect k=2 (95% confidence) for reporting
  • Document all your uncertainty sources for quality system records

Practice Examples

Example: Metal Content Analysis (mg/L)

A laboratory analyzing the copper content of a water sample.

Type A Data (Repeated Measurements) 
5.82
5.76
5.85
5.79
5.81
5.78
5.83
5.80
5.77
5.84
Type B Sources
  • 📊 Calibration uncertainty: ±0.15 mg/L (Normal)
  • 🧪 Reference material: ±0.1 mg/L (Rectangular)
  • 🌡️ Temperature effect: ±0.05 mg/L (Rectangular)
Example: Pipette Calibration (µL)

Calibration of a 1000 µL pipette using gravimetric method.

Type A Data (Repeated Measurements) 
998.2
1001.5
999.8
1000.3
997.9
1001.1
999.4
998.7
1000.6
999.2
Type B Sources
  • ⚖️ Balance calibration: ±0.2 µL (Normal)
  • 🌡️ Temperature effect: ±0.3 µL (Rectangular)
  • 💨 Evaporation: ±0.1 µL (Rectangular)
Example: pH Measurement

pH measurement of an environmental water sample.

Type A Data (Repeated Measurements) 
7.41
7.39
7.42
7.40
7.38
7.41
7.40
7.39
7.42
7.40
Type B Sources
  • 📏 pH meter calibration: ±0.02 pH (Normal)
  • 🧪 Buffer uncertainty: ±0.01 pH (Normal)
  • 🌡️ Temperature effect: ±0.015 pH (Rectangular)
Expected Outcomes:

When using these examples with k=2 (95% confidence level), you should expect:

  • Chemical Analysis: Approximately ±0.18 mg/L expanded uncertainty
  • Volume Measurement: Approximately ±2.1 µL expanded uncertainty
  • pH Measurement: Approximately ±0.03 pH expanded uncertainty
🎯 Type A Uncertainties (Statistical Analysis)
⚙️ Type B Uncertainties (Systematic Effects)
🎪 Combined & Expanded Uncertainty