Combine weighing and volume uncertainty for concentration
Combine standard uncertainties for formulas such as C=m/V, C=(m·P)/V, and C=(m·P)/(M·V).
Calculate concentration and dilution uncertainty from weighing error, volume error, and related inputs directly in your browser.
Review combined standard uncertainty uc, expanded uncertainty U=k·uc, main contributors, and report-ready output in one place.
Combine standard uncertainties for formulas such as C=m/V, C=(m·P)/V, and C=(m·P)/(M·V).
Handle certificate-style ±a(k=2), specification-style ±a, and triangular assumptions without a separate manual conversion.
The contributor breakdown shows which factor dominates the variance, so you can target improvements efficiently.
Switch among plain text, Markdown, CSV, and JSON, then copy the exact format you need.
m=100.00 mg ±0.10 (rectangular), V=100.00 mL ±0.08 (normal, k=2)
Shows concentration, uc, U, and the contribution split between m and V.
C1=1000 mg/L ±5, V1=10.00 mL ±0.02, V2=100.00 mL ±0.08
Shows U for the diluted concentration and which volume error matters most.
A=98.0 ±0.5, B=100.0 ±0.2
Shows uncertainty for A/B or Recovery(%).
Enter m, P, M, and V together
Shows the contribution from purity and molar mass as well.
The standard-deviation-like uncertainty associated with an input quantity x.
The standard uncertainty of result y after all input contributions are combined.
The report-facing uncertainty calculated as U = k·uc.
A coefficient showing how strongly the result changes when one input changes.
The share of total variance attributable to one factor.
Standard uncertainty conversion: u=a/k, a/√3, or a/√6Combined standard uncertainty: uc = √Σ(cᵢ·uᵢ)²Expanded uncertainty: U = k·ucConcentration: C = m/V, (m·P)/V, or (m·P)/(M·V)Dilution: C2 = C1·V1/V2Ratio: R = A/BYes. Choose a distribution assumption to convert tolerance notation into standard uncertainty: u=a/k for normal(k), u=a/√3 for rectangular, or u=a/√6 for triangular.
k=2 is common, but follow your standard, internal rule, or customer requirement. The chosen k is always shown in the result.
Yes. Copy plain text, Markdown, CSV, or JSON; the output includes assumptions, inputs, results, and the main contributors.
The first release assumes independent inputs. With correlated inputs, the result may be under- or over-estimated.
This calculator uses first-order propagation. For large relative uncertainties or strongly nonlinear formulas, verify the result with another method.