Ordered pressure traceOne point per recorded interval
Unit Converters
Pressure Range Calculator
Convert an ordered pressure series to one target unit and calculate range, mean, extrema, sample standard deviation, and a record-preserving trend.
Record order is evidence: enter readings in acquisition order. The calculator reports the pressure statistics, while the sequence chart reveals ramps, spikes, and settling that an average can hide.
Records-
Mean pressure-
Minimum-
Maximum-
Range-
Sample deviation-
PRESSURE RANGE
Read variability and sequence together
The ordered line retains process movement; the ledger shows the exact converted row values used for mean, extrema, range, and sample deviation.
| Record | Raw | Converted | Deviation from mean | Review note |
|---|
How to use
Summarize a pressure run without deleting its time order
This page is for a comparable series from one instrument, one unit basis, and one operating mode. It supports stability screening; it is not a substitute for a process capability study.
- Paste readings in the order they were acquired, one value per line or comma.
- Select the source unit and the unit used by the report.
- Enter the sampling interval so operators can relate excursions to time.
- Read minimum, maximum, range, and sample deviation together.
- Return to the sequence plot before concluding that the process is stable.
Range fundamentals
Statistics answer different questions
Calculation method
Convert each row before calculating
pᵢ,t = pᵢ,s × f(s)/f(t)μ = Σpᵢ,t / nR = max(pᵢ,t) − min(pᵢ,t)s = √[Σ(pᵢ,t − μ)²/(n − 1)]Conversion and statistics use unrounded values; display formatting happens at the end.
Default substitution
For 120, 145, 168, 192, 225, 248 kPa, the converted bar values are 1.200 through 2.480. Mean = 1.830 bar, range = 1.280 bar.
Reconciliation
The total of the six converted values divided by six must equal the displayed mean. The range must equal maximum minus minimum; a mismatch indicates premature rounding or a row error.
Deep dive: outliers
One spike can dominate the range
Range is useful for finding extremes but should not be treated as a probability interval. Investigate a spike against the raw trace and operating event before removing it.
Deep dive: sampling
Intervals define what the trace can see
A one-minute sample cannot prove that a millisecond pressure surge did not occur. Keep the interval and acquisition bandwidth with the result.
Deep dive: comparability
Do not average unlike regimes
Mixing startup, steady state, and shutdown readings produces a number with little operational meaning. Segment the run when the process state changes.
Cases, limits, and glossary
Use the series to decide what to inspect next
Pump commissioning: a rising sequence with a narrow spread may indicate normal ramp-up, not instability.
Maintenance check: a lower deviation after seal replacement supports a stability hypothesis, but it does not prove causality without matched runs.
- Does not estimate a distribution outside the observed run.
- Does not identify a process capability index without specification limits.
- Does not correct drift, autocorrelation, or missing samples.
- Glossary: excursion, baseline, range, sample deviation, interval, outlier.
FAQ
Why preserve order? Because the average cannot show a ramp or oscillation.
Should I use population deviation? Use n − 1 when the run is a sample of ongoing operation; document another choice.
Can I mix gauge and absolute values? No, reconcile the datum first.
Does a small range prove control? No; it may reflect a short or poorly sampled window.
Result interpretation
Read center, spread, and acquisition order together
Mean describes the arithmetic center of the entered run, minimum and maximum identify observed extremes, range shows the full observed span, and sample deviation summarizes dispersion around the mean. None of those statistics shows whether the sequence ramped, cycled, drifted, or contained a brief transient; the ordered trace answers that separate question.
- A narrow range can still hide a steady drift when the run is short.
- A large range may be caused by one event rather than persistent instability.
- A zero range means every entered value is identical at the available resolution.
- Sample deviation is undefined for fewer than two valid observations.
Detailed calculation process
Convert row values first, then summarize unrounded data
pi = si x f(source) / f(target)mean = sum(pi) / nrange = max(pi) - min(pi)s = sqrt[sum((pi - mean)^2) / (n - 1)]pi is each converted pressure; n is the count; s is sample standard deviation.
| Step | Calculation | Result | Unit |
|---|---|---|---|
| Convert | 120, 145, 168, 192, 225, 248 kPa | 1.20, 1.45, 1.68, 1.92, 2.25, 2.48 | bar |
| Count | number of valid rows | 6 | dimensionless |
| Mean | 10.98 / 6 | 1.83 | bar |
| Range | 2.48 - 1.20 | 1.28 | bar |
- Parse valid pressure rows without sorting them.
- Convert every row to the selected target unit using unrounded factors.
- Count the valid converted observations.
- Sum the six converted values to obtain 10.98 bar.
- Divide by six to obtain a mean of 1.83 bar.
- Select 1.20 bar and 2.48 bar as the observed extrema.
- Subtract extrema to obtain a 1.28 bar range.
- Compute squared deviations and divide by n - 1 for sample deviation.
- Reconcile the ledger total and extrema with the displayed summary.
Evidence and sampling
Keep the sequence metadata with the values
Retain acquisition timestamps, sampling interval, instrument and channel IDs, pressure datum, operating state, missing-row policy, resolution, and any filtering applied by the logger. Segment startup, steady-state, and shutdown runs instead of averaging unlike regimes.
Scope and limitations
Observed spread is not a process guarantee
- The entered run does not establish future distribution or design extremes.
- Range is sensitive to one extreme and does not express probability.
- Sample deviation does not correct autocorrelation, drift, or missing samples.
- Capability indices require approved specification limits and a suitable process model.
- A sampling interval cannot reveal events faster than the acquisition system can capture.
Practical examples
Sequence changes the operational conclusion
Pump startup: a smooth rise from 120 to 248 kPa has a wide range because the machine is ramping, not because steady-state control is poor.
Post-maintenance check: two matched steady-state runs can compare spread, but a lower deviation alone does not prove the repair caused the change.
Key terminology
Pressure range glossary
- Mean
- The arithmetic center of all valid converted observations.
- Extremum
- The observed minimum or maximum in the entered run.
- Range
- Maximum minus minimum, expressed in the target pressure unit.
- Deviation
- The distance of one observation from the run mean.
- Sampling interval
- The time between successive acquired readings.
- Autocorrelation
- Dependence between observations caused by their sequence in time.
Frequently asked questions
Why preserve the original reading order?
Sorting would erase ramps, oscillations, and event timing that the summary statistics cannot show.
Should I use sample or population deviation?
Use sample deviation when the entered run represents a sample of ongoing operation; document another convention when the complete population is known.
Can gauge and absolute values be mixed in one run?
No. Reconcile every row to the same pressure datum before calculating the statistics.
Does a small range prove the process is controlled?
No. The run may be too short, undersampled, filtered, or taken during only one operating regime.
Important note
Before relying on this result
Statistics do not replace process limits, uncertainty analysis, or time-series review.