Filter Size Calculator
The formula
What the filter size tells you
The size and shape of the move between two figures — total percent, absolute delta and the annualised rate — for filter size.
Calculation: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Enter your inputs and every substitution is shown below the result.
Reading the result
Compare the annualised line with the same measure from a rival or a baseline; the raw percent flatters long periods and punishes short ones.
Limitations and best practice
Percentage-point vs percent confusion: a move from 4 % to 6 % is +50 % relatively but +2 points — state which you mean.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Is percent change symmetric?
Why annualise?
Source & methodology
Standard growth arithmetic.
Filter Size explained: formula, worked example and honest limits
You are here because you need a specific number, and you want to see how it was produced before you rely on it. There are plenty of pages about Filter Size; almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
The number itself is the easy part. What takes judgement is knowing which inputs are facts in your situation and which are guesses wearing a decimal point — a distinction this page makes explicit for every field above.
It helps to separate the mechanics from the interpretation. The mechanics are fixed: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Anyone, anywhere, entering the same inputs will get the same 21.70%. The interpretation is where experience counts: whether 21.70% is good, normal or alarming depends on comparisons covered below, and that is the part most articles about Filter Size never explain.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here filter size = 21.70%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Before first, at ≈62.3 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
Every input in Filter Size, and what it does to the answer
One formula, published in full: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Before (example value 106) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
After (example value 129) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Periods between (years) (example value 4) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Use the value as of today, not as of the last time you looked — time fields drift silently.
The default Filter Size calculation, written out in full
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Before, After, Periods between (years). The endpoint of that chain is 21.70% of filter size, sitting in the “Solid growth” band.
- Δ = 129.00 − 106.00 = 23.00
- Percent = 23.00 ÷ 106.00 × 100 = 21.70 %
- Annualised = (129.00 ÷ 106.00)^(1/4.0) − 1 = 5.03 %
Absolute change — 23.00. This is the number experienced users quote when the headline alone would mislead.
Per-period (annualised) — 5.03%. Compare it against the main result of 21.70% before drawing conclusions.
Multiple — 1.22 ×. Compare it against the main result of 21.70% before drawing conclusions.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
How far Filter Size can reasonably move
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of Filter Size, not an interpolation.
| Before setting | Filter Size |
|---|---|
| 80 % of the example value | 52.12% |
| 90 % of the example value | 35.22% |
| example inputs | 21.70% |
| 110 % of the example value | 10.63% |
| 120 % of the example value | 1.42% |
Across 5 settings of Before, the result spans 1.42% to 52.12%. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing Before alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Filter Size the most
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the filter size recomputed, so the ranking below is measured rather than asserted. For Filter Size the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Nudge Before by ±10 % and Filter Size lands between 10.63% and 35.22% (sensitivity ≈62.3 %)
- Nudge After by ±10 % and Filter Size lands between 9.53% and 33.87% (sensitivity ≈56.1 %)
Before is the dominant lever here: ten percent either way moves the result by about 62.3 %, from 10.63% to 35.22%. Spend your verification effort there first, and treat After as the second priority (≈56.1 % per ten percent). The remaining fields can sit at safe defaults without materially changing the answer — knowing which is which is what separates a careful calculation from an anxious one.
Reading the result: bands, zones and thresholds
A number on its own is trivia; a number against a range is intelligence. On the example inputs the band reads “Solid growth”; your own figures place you on a different rung of the same ladder. Before treating the band as fact, note its width: ten percent either way on Before already spans 10.63% to 35.22%. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
Set Filter Size beside its neighbours and it usually plays a specific role: this figure establishes the size of something, and the neighbouring tools establish whether that size is acceptable. Skipping the first step makes the second one arbitrary.
Why Filter Size results go wrong — and how to prevent it
Percentage-point vs percent confusion: a move from 4 % to 6 % is +50 % relatively but +2 points — state which you mean. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reusing a Filter Size from last season. In Construction & Home Improvement the inputs are the thing that drifts; the formula does not.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Before first, everything else second.
A final trap is presentation: reporting Filter Size to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Filter Size verification checklist
- Note the date and the inputs beside the number so the figure can be audited later.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Put Before under a magnifier; the sensitivity table above is the reason why.
- Compare the result with one independent method or published benchmark.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
A routine for decision-grade Filter Size
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for Filter Size takes a minute to learn and applies to every input above.
Step 1 — one document, one pass. Open the statement, label or record that holds before, after, periods between (years) and transcribe straight into the form. Transcription from a single source removes the mismatch errors that appear when figures are assembled from three different places. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. A result worth acting on survives having its two shakiest inputs halved.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. Compare the calculation to the rough guess you arrived with, and ask why they differ.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. The input you reach for first is usually the one you measured longest ago.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 21.70% output. Six months from now the context is what turns this figure into a trend. The inputs are the part of the work that nobody else can do for you.
Who actually uses Filter Size — and when
Most MEP Systems disagreements are arithmetic disagreements in disguise. When Filter Size of 21.70% sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
The companion outputs — Absolute change and Per-period (annualised) — exist for the second stage of that screen: the headline sizes the prize, while the companions describe the trade-off you are accepting to get it. The test of a good estimate is not that it feels right but that it changes what you do.
There is a personal-administration use people overlook: periodic self-checking. Filter Size quietly drifts as life changes — rates move, bodies change, costs compound — and re-running it a few times a year catches drift while correction is still cheap. Estimates improve most when the worst case is written down in ink.
The questions that come up most about Filter Size
What affects Filter Size the most?
Measured on this engine, Before is the dominant lever: moving it ±10 % shifts the filter size across 10.63% to 35.22% — about 62.3 % of the headline, with After next at ≈56.1 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: after or before?
Before, by a factor of about 1.1. Concretely: ten percent on Before is worth ≈62.3 % of Filter Size, the same nudge on After only ≈56.1 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Filter Size?
With the example inputs on this page the result is 21.70%, labelled “Solid growth”. “Typical” varies with situation, which is why every result here ships with its verdict band and its sensitivity list: they turn one figure into a range you can locate yourself inside.
How do I calculate Filter Size by hand?
Use the stated model — change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1 — and substitute in the order the tool prints (it starts from Δ = 129.00 − 106.00 = 23.00). On the example inputs the hand route lands on 21.70%, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Filter Size if before changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the filter size goes across 10.63% to 35.22%, a swing of roughly 62.3 % around the 21.70% baseline. That ratio is the practical definition of how much this input matters.
Is the Filter Size result of 21.70% good or bad?
The tool answers “what”, not “whether”: 21.70% carries the verdict “Solid growth” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
Can Filter Size be negative or empty?
Yes, and that is informative rather than broken: a negative Filter Size usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
Do I add waste to Filter Size?
Yes — standard waste allowances run 5–15 % depending on material and cut complexity, and this tool expects them inside your inputs. Leaving waste out is the most frequent way a Filter Size under-orders.
Is percent change symmetric?
No — up 25 % needs down 20 % to undo. The multiple output keeps the round trip honest.
Why annualise?
It puts unequal time spans on one scale, making 4-year and 9-month comparisons legible.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
What the labels on this page mean
- Absolute change
- 23.00 on the example inputs — a companion figure printed beside the headline of Filter Size so that no result is read in isolation.
- Per-period (annualised)
- 5.03% for the Filter Size worked case; it sits next to the main result because it carries context the headline leaves out.
- Multiple
- 1.22 × on the example inputs — a companion figure printed beside the headline of Filter Size so that no result is read in isolation.
- Filter Size
- The primary output of this tool: 21.70% for the default inputs, computed exactly from change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1.
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- The interpretation attached to a result (“Solid growth” on these inputs), which turns a bare number into a position on a scale.
- Sensitivity (±10 %)
- How far the Filter Size moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the Filter Size model comes from
Everything above runs on one stated formula, applied without hidden coefficients: change % = (after − before) ÷ before × 100; annualised = (after ÷ before)^(1/periods) − 1. Source of record: Standard growth arithmetic. Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. What that buys you is reproducibility — two people, two browsers, the same arithmetic, and a printed trail from inputs to result that either of them can audit.
Next steps after the calculation
Save the number together with its inputs and today’s date; a Filter Size figure without context is unusable the moment an input changes.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Construction & Home Improvement, a dated figure is a trend, and an undated one is a rumour.