Uncertainty Guide

Uncertainty Propagation for Addition and Subtraction

The simplest case in error propagation - but with one surprising twist that trips up most students.

5 min read🎓 University level🔬 Lab report focused

The Rule for Addition and Subtraction

For any formula involving addition or subtraction:

f = x + y   or   f = x − y

The propagated uncertainty is:

Δf = √[ (Δx)² + (Δy)² ]

This is called adding uncertainties in quadrature - you square each uncertainty, sum them, then take the square root. Notice that both addition and subtraction follow the exact same rule. Whether you add or subtract two quantities, their absolute uncertainties always combine in the same way.

The Surprising Twist - Subtraction Doesn't Help

Students often assume that subtracting two quantities reduces uncertainty. It doesn't. The formula is identical for addition and subtraction - Δf = √[(Δx)² + (Δy)²].

In fact, subtraction can dramatically worsen relative uncertainty. If you subtract two nearly equal numbers, the result is small but the absolute uncertainty stays the same - making the relative uncertainty (Δf/f) very large. This is called catastrophic cancellation.

Worked Example

Let's calculate the total length of two rods placed end to end.

L₁12.3 ± 0.2 cm
L₂8.7 ± 0.3 cm

Step 1 - Compute the result:

L_total = 12.3 + 8.7 = 21.0 cm

Step 2 - Apply the rule:

ΔL = √[ (0.2)² + (0.3)² ]
ΔL = √[ 0.04 + 0.09 ]
ΔL = √0.13
ΔL ≈ 0.36 cm

Step 3 - Round and report:

L_total = 21.0 ± 0.4 cm

The uncertainty is rounded to 1 significant figure, and the result is rounded to match.

More Than Two Variables

The rule extends naturally to any number of terms. For f = x + y + z + ..., the propagated uncertainty is:

Δf = √[ (Δx)² + (Δy)² + (Δz)² + ... ]

Each additional variable contributes its squared uncertainty under the square root. The more variables you add, the larger the combined uncertainty - but it grows more slowly than linear addition would suggest, because of the square root.

Common Mistakes to Avoid

Adding uncertainties directly

Writing Δf = Δx + Δy instead of √(Δx² + Δy²) overestimates uncertainty. Direct addition assumes errors always act in the same direction simultaneously. Use quadrature for independent random errors.

Using relative uncertainties for addition

For products and quotients, you use relative uncertainties (Δx/x). For sums and differences, you must use absolute uncertainties (Δx). Mixing these up is one of the most common errors in lab reports.

Assuming subtraction reduces uncertainty

As shown above, subtracting two quantities with similar values can produce catastrophically large relative uncertainties. Always compute and report the relative uncertainty of your final result.

Quick Reference

OperationFormulaUncertainty Rule
Additionf = x + yΔf = √(Δx² + Δy²)
Subtractionf = x − yΔf = √(Δx² + Δy²)
Three termsf = x + y + zΔf = √(Δx² + Δy² + Δz²)
Constant addedf = c + x (c exact)Δf = Δx

Frequently Asked Questions

Q1Do I add uncertainties directly or in quadrature for addition?

Always in quadrature for independent random uncertainties: Δf = √(Δx² + Δy²). Direct addition is only used as a conservative worst-case estimate, and most university physics labs require quadrature.

Q2Why does subtraction give the same uncertainty as addition?

Because the uncertainty formula uses partial derivatives, and the partial derivative of both (x + y) and (x − y) with respect to each variable is ±1. The sign disappears when squared, so addition and subtraction are identical in terms of uncertainty propagation.

Q3What if one of my uncertainties is much larger than the other?

The larger uncertainty dominates. For example, if Δx = 1.0 and Δy = 0.1, then Δf = √(1.0² + 0.1²) ≈ 1.005 - almost identical to just using Δx alone. This is a useful check: if one uncertainty is 3× or more larger than the others, the others barely matter.

Q4Can I use this rule for more than two variables?

Yes. For f = x₁ + x₂ + ... + xₙ, the rule is Δf = √(Δx₁² + Δx₂² + ... + Δxₙ²). Just add all squared uncertainties under the square root.

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