PlanMaker STANDARDIZE: Reference Scores and Unit Conversion
Standardize measurements in PlanMaker with fixed reference parameters, Celsius-to-Fahrenheit controls and the official numerical example.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
STANDARDIZE expresses a measurement’s distance from a supplied mean in units of a supplied standard deviation. You choose both reference parameters. The function does not infer a population, calculate a mean from neighboring cells or decide whether a measurement is acceptable.
Availability and version history
- Introduced: Documented by the PlanMaker 2010 manual; the first introduction release and date are not established.
- Availability: Documented in PlanMaker 2026; this is not a final working-version endpoint.
- Scope: The reference belongs to the 2026/NX manual family. FreeOffice and individual mobile-build availability remains unverified.
- Checked: October 14, 2026, against the official function reference and historical entry. Examples were independently calculated; no native PlanMaker test was performed.
Syntax and reference parameters
=STANDARDIZE(x, Mean, StdDev)
The PlanMaker reference gives three arguments: the value to standardize, the arithmetic mean and the standard deviation. None is shown as optional.
The mathematical calculation is (x-Mean)/StdDev. NIST’s explanation of standardized scores describes this distance in standard-deviation units. The examples below use a positive standard deviation. Zero makes the mathematical division undefined; the short PlanMaker entry does not specify every native diagnostic or invalid-parameter boundary.
Example: a fixed temperature reference
Create ReferenceTemperature. Put Temperature, STANDARDIZE and Direct check in A1:C1. Enter 16,18,20,22,24 in A2:A6. Put Reference mean in E2 and Reference standard deviation in E3, with 20 in F2 and 2 in F3. All three quantities use degrees Celsius.
Enter =STANDARDIZE(A2,$F$2,$F$3) in B2 and =(A2-$F$2)/$F$3 in C2. Fill B2:C2 through row 6.
| Row | Temperature | Expected B and C |
|---|---|---|
| 2 | 16 | -2 |
| 3 | 18 | -1 |
| 4 | 20 | 0 |
| 5 | 22 | 1 |
| 6 | 24 | 2 |
The result 2 means two specified standard deviations above the specified mean. It does not mean two degrees, twice the mean or a probability of 2. The negative results represent values below the reference mean.
Put Reconstructed temperature in D1. Enter =$F$2+B2*$F$3 in D2 and fill to D6. Expected results are 16,18,20,22,24, reconstructing the original measurements from the standardized distances.
The reference standard deviation of 2 is an input chosen for this example. It has not been estimated from the five displayed observations. To use an estimated sample or population spread instead, calculate that parameter deliberately and explain the population your analysis describes.
Convert the units, including the standard deviation
Create UnitConversion. Put Fahrenheit temperature and Standardized result in A1:B1. Enter 60.8,64.4,68,71.6,75.2 in A2:A6. These are the same five temperatures after applying Celsius*9/5+32.
The transformed mean is 68 and the transformed standard deviation is 3.6. Enter =STANDARDIZE(A2,68,3.6) in B2 and fill through B6. Expected results remain −2,−1,0,1,2.
A shift affects the mean but not the spread. The standard deviation changes by the scale factor 9/5; you do not add 32 to it. To see the effect of that mistake separately, put =STANDARDIZE(75.2,68,35.6) in D2. The result is approximately 0.2022471910, rather than 2. Here 35.6 is the incorrect value obtained by adding 32 to the correctly scaled standard deviation.
This comparison is an arithmetic unit-conversion check. It does not provide evidence that the original measurements were normally distributed or calibrated correctly.
Changing the reference changes the interpretation
Return to ReferenceTemperature without changing F2:F3. In H2 enter =STANDARDIZE(24,22,2); expect 1. In H3 enter =STANDARDIZE(24,20,2); expect 2. The measurement and standard deviation are identical, but the reference mean changed.
In H5 enter =STANDARDIZE(120,100,20); expect 1. The raw value 120 is larger than 24, yet its standardized distance from its own reference is smaller than H3’s. Comparing such scores meaningfully requires compatible measurement purposes and reference populations. The arithmetic alone cannot establish a fair ranking.
Reproduce the official example
On a separate VendorStandardize sheet, put 5 in A1, 4 in A2 and 1.25 in A3. Enter =STANDARDIZE(A1,A2,A3) in C1. The expected result is 0.8, exactly matching the example printed in both the current help and the checked 2010 manual. The direct calculation is (5-4)/1.25.
Practical limits
A standardized value is not automatically a percentile, probability or reason to remove an observation. NIST’s outlier discussion explains why interpretation depends on distributional assumptions. Standardizing arbitrary data does not make its shape normal.
Keep the supplied standard deviation positive and the measurement, mean and spread in compatible units. This guide does not assign undocumented error tokens for nonnumeric inputs, zero or negative spread, missing arguments or extreme values. English examples use commas; follow the argument separator accepted by your PlanMaker installation.