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Library / Probability distributions / PRD-16

Probability distributions

Lognormal measurement: fraction below a threshold

Fraction of a lognormal population at or below a threshold x.

Ref
PRD-16
Rev
v1
Field
Probability distributions
Result
F

The fraction below a threshold is the standard normal cumulative function Φ evaluated at ln(x/m)/s. At x = m the argument is zero and the fraction is exactly one half, since m is the median. A nonpositive threshold gives zero.

Fraction of a lognormal population at or below a threshold x. Φ is the standard normal cumulative function, so at x = m the fraction is exactly one half.

Calculator

Solve for
µm
150
0.11.5
µm
0.550
  • Standardised log, ln(x/m)/s0.3646
  • Fraction above x, 1 − F0.3577
  • Threshold exceeded by 5 %, m e^(1.645 s)22.76 µm

What drives the result

Each variable is moved across its typical range while the others stay at the values above. The longest bar is the key driver.

Fraction at or below x () current value 0.6423
xThreshold xKey driver
1.04e-90.999
mMedian m
0.002161
sLog spread s
0.5480.966
  • About 64.2 % of the population lies at or below 12 µm, and 35.8 % above it.
  • Because the scale is logarithmic, equal ratios of x to the median shift the standardised value by equal steps: a factor of 1.65 above the median adds one standard deviation.
Chart data as tables

Ranked variables

VariableTypical rangeLowest resultHighest resultSwing ()Local stepChange in result
x Threshold x0.5 to 50 µm1.04e-90.99940.9994+10%+10.6 %
m Median m1 to 50 µm0.00215710.9978+10%−11.4 %
s Log spread s0.1 to 1.5 0.54840.96590.4175+10%−1.94 %

Sweep of Threshold x

Threshold x (µm)Fraction at or below x
0.51.04e-9
6.6880.2105
12.880.6934
19.060.9015
25.250.968
31.440.989
37.630.996
43.810.9984
500.9994

Sweep one variable

Fraction at or below x ()Hover, touch, or use the arrow keys on the chart
00.20.40.60.81 1020304050 Threshold x (µm) now 0.6423

Variables and how each one contributes

F

Fraction at or below x

Result ·

What the equation gives you. Everything else feeds it.

m

Median m

µm · typical 1 to 50

The median of the quantity, in µm: half the population is below it. The logarithm of the quantity is normal with mean ln m. Stretches the whole distribution in proportion. Raising it by 10 % (to 11) moves the result by −11.4 %, from 0.6423 to 0.5691.

s

Log spread s

· typical 0.1 to 1.5

The standard deviation of the natural logarithm, a plain number. Roughly, s = 0.5 means a typical factor of about 1.65 either side of the median. Controls the spread and the length of the upper tail; the effect is steep at large s. Raising it by 10 % (to 0.55) moves the result by −1.94 %, from 0.6423 to 0.6299.

x

Threshold x

µm · typical 0.5 to 50

The threshold, in µm, at which the result is read. Moves the point at which the density or the fraction is evaluated. Raising it by 10 % (to 13.2) moves the result by +10.6 %, from 0.6423 to 0.7106.

Worked example with the values above

  1. Ratio: x/m = 12 / 10 = 1.2.
  2. Standardise: z = ln(1.2) / 0.5 = 0.36464.
  3. F = Φ(z) = 0.64231.

Assumptions and limits

  • The quantity is strictly positive and its logarithm is normally distributed.
  • The median m and the log spread s come from data on the same population.

Common mistakes

  • Using the standard deviation of the raw data as s: s is the standard deviation of ln x.
  • Using log base 10 values in place of natural logs: s changes by a factor of ln 10.
  • Quoting the median as the average when the mean is larger.

Statistics and uncertainty

The inputs are parameters, usually fitted to data, and their estimation error carries into the result. The probability or density is a smooth function of the parameters, so the sweep chart shows how sensitive it is: where the curve is steep, a small error in a parameter makes a large difference. The formula treats the parameters as exact, so it gives no confidence interval on its own.

Where it is used

  • Particle and droplet size distributions, concentrations of contaminants, and material strengths and fatigue lives.
  • Repair times and other positive, right-skewed engineering quantities.

Maths you need

  • Natural logarithm: the inverse of e to a power
  • Normal distribution: the bell curve and its cumulative function

Related formulas

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