Read What Your Result Actually Means
You can now compute the quantities Part 1 and the last chapter set out: totals and shares, an honest average, percentages and change, and fair rates. But a number does not explain itself. Once you have a correct figure, the next job is to say plainly what it means, because a right answer read the wrong way can still lead you astray. This chapter is about that reading: stating what your own result does, and does not, tell you.
Why a Correct Number Still Needs Reading
Imagine you poll your local choir and find that 70% picked Saturday for rehearsals. The figure is correct, yet within a minute someone announces, “everyone wants Saturday, so that’s settled.” The number never said that. It said something narrower, and the gap between what it said and what people heard is exactly where good decisions go wrong.
A computed result is silent. It sits on the page as a single figure, and people fill that silence with whatever story feels natural, usually a bigger, bolder claim than the number can support. Your task is to speak for the number before anyone else does, stating its real meaning so it cannot be stretched into something it never measured.
I calculated it correctly, so isn’t the meaning obvious?
Not quite. Correctness tells you the arithmetic is sound; it says nothing about how far the result can be pushed. The same correct 70% can be reported honestly or wildly overstated, and the difference is entirely in the reading, not the math.
What “Interpreting a Result” Means
Interpretation sounds grand, but for everyday numbers it is a small, concrete act you can do in a few sentences.
Notice that interpretation is not more calculation. You are not producing another figure; you are putting the figure you already have into honest words, so that its scope, and its limits, travel with it wherever it goes.
State What Your Result Does and Does Not Say
Whatever the number, the same four moves turn it from a bare figure into an honest statement.
Name the quantity and its unit, so it is clear what kind of number this is (a total, a share, an average, a rate).
State the group and the period it covers, because every result is about some specific people or things over some specific stretch of time.
Say in plain words what it measures, the one thing it genuinely tells you.
List what it cannot claim: it rarely speaks for a whole population, for the future, for every individual, for other groups, or for why something happened.
Do those four in order and you will almost never over-read a result, because the fourth move forces you to name the limits out loud instead of quietly ignoring them.
See It in Action: A Choir’s Rehearsal Poll
Your community choir has 24 members. You ask them all one question, “which day suits you best for rehearsals?”, and 20 reply. Of those 20, 14 choose Saturday, so you compute a share: 14 ÷ 20 × 100 = 70%. Now read that 70% with the four moves.
Quantity and unit: it is a share, a percentage, not a count of people. Fourteen people is the count; 70% is their share of the responses.
Group and period: it covers the 20 members who answered this one poll, at this one moment, not all 24 members and not the choir forever.
What it measures: among those who replied, Saturday was the most-picked option out of the days you offered.
What it cannot claim: it does not say 70% of the whole choir prefers Saturday (four people never answered), nor that Saturday is genuinely “best” (it was only the most-picked among the choices you listed), nor that those members will still prefer it next season, nor why they chose it.
Put honestly, the result is: “Of the 20 members who responded, 70% picked Saturday as their preferred rehearsal day among the options offered.” That sentence is unassailable. “Everyone wants Saturday” is the same number stretched past what it can carry.
Your Turn!
Over the summer, your community garden logged the harvest, and you computed that the average yield was 3.1 kg per plot across the 12 plots. You also notice that one standout plot produced 9 kg while most plots came in around 2 kg.
Do the following, writing your answers down before you check:
Write one plain sentence stating what the 3.1 kg average measures, and over what group and period.
Name two things this average cannot claim.
Given that one plot hit 9 kg while most produced around 2 kg, what does that tell you about calling 3.1 kg a “typical” plot? Link your answer to what you learned about the mean and the median.
Then check your answer against the model solution found at the end of this chapter.
Let’s Recap!
A computed result is silent, so people fill the gap with claims bigger than the number supports.
Interpretation means stating, in plain words, what a result measures, over what group and period, and what it cannot claim.
Interpretation is not more calculation; it is putting the figure you already have into honest language.
The four moves are: name the quantity and unit, state the group and period, say what it measures, and list what it cannot claim.
Reading your own result is distinct from reading someone else’s chart, which the companion course covers.
You can now read what a single result does and does not say. Next you will turn that habit outward into a repeatable set of correctness checks, so you catch your own mistakes before you ever trust, or share, a number.
Model Solution
A fair sentence: “Across the 12 garden plots this summer, the average (mean) harvest was 3.1 kg per plot.” It measures the mean yield, for these 12 plots, over this one growing season.
Two honest limits (any two): it cannot claim every plot produced near 3.1 kg (the spread is wide); it cannot predict next summer’s yield; it cannot say why the plots differed (watering, sun, soil); and it cannot speak for plots in other gardens.
With one plot at 9 kg and most around 2 kg, the single high plot is an outlier that drags the mean upward, so 3.1 kg is not a “typical” plot, most plots produced less. As you saw in the mean-versus-median chapter, the median (a middle value near 2 kg) would describe a typical plot more honestly here, so calling 3.1 kg “typical” over-reads the average.
