Audit a percentile before calling it your rank

Choose a value threshold or a rank question

A75 th-percentile value asks for a threshold in the measured distribution. The share of observations below a target asks a different question. State whether larger values mean more displays, more response or a longer unwanted delay; a high numeric rank is not automatically better content.

Keep posts, creators, sessions and people separate. Several posts from one creator can weight that creator more heavily in a post sample. An own-history calculation cannot establish a LinkedIn-wide rank, and a missing measurement is not an extra zero to add to the sorted sample.

Read the actual interpolation convention

NIST notes that there is no universally adopted sample-percentile interpolation. For the labeled R7 method, the one-based position is 1+p(n−1); for R6 it is p(n+1), with the stated endpoint treatment. Interpolate between the adjacent ordered values when the position is fractional.

Record the method, p, sample size and function/version used rather than assuming every spreadsheet percentile command is identical. Methods can agree at the median but differ far into a small sample. Changing the convention after seeing a favorable threshold changes the report and needs a visible note.

Keep strict-below and at-or-below counts distinct

For the constructed values 10,20,20,20,30 and target 20, one of five values is strictly below and four of five are at or below:20% and 80%. The tie convention determines how a rank-style percentage is reported. Do not choose whichever endpoint makes the author look more exceptional.

An interpolated value quantile may not be one of the original observations. That is a defined calculation, not a newly measured post. Keep threshold direction and equality handling when selecting a top group, otherwise tied records can be excluded arbitrarily.

Resolve three constructed percentile claims

P1 — Constructed sorted sample 0,10,20,30,100. At p=0.75, R7 uses position 4 and gives 30; R6 uses 4.5 and gives 65. Decision: report the actual method with the threshold. Outcome: two specified calculations on five values, not evidence that a tool recovered different source data.

P2 — Constructed ties 10,20,20,20,30 at target 20. Decision: retain 20% strictly below and 80% at-or-below, or a separately declared tie-aware convention. Outcome: do not call the target unambiguously top 20% or a better creator without defining the question and population.

P3 — Constructed sample mismatch: one export contains only the most recent posts, another the selected highest-response posts. Decision: resolve selection before treating different percentiles as a performance change. Outcome: sorting and precise interpolation do not repair incomparable or cherry-picked samples.

Keep the summary within its measured sample

A middle 50% range or sample percentile is not a confidence interval for a population parameter or a prediction interval for the next post. Estimating those requires additional methods and assumptions. A small number of decimal places can be more honest than displaying excessive precision from a few observations.

Read the original posts near a threshold if the purpose is an editorial decision. A high impression value is exposure evidence, not proof of clarity, preference or revenue. A quantile can organize a review; it cannot replace the reader task or explain why the count occurred.

Save the convention and complete ordered values

The worksheet records source/unit, selection, missing values, ordered sample, p, method, target/tie rule and bounded interpretation. The offline packet reproduces the two interpolation methods and tie counts using constructed inputs; it is not an importer or a population-ranking service.

Primary statistical definitions were read on 1 November 2026. All examples are invented exercises. No creator benchmark, private account observation, prediction or independent reader judgment is established.