ds@mcpanalytics.aiA data scientist you can email your data and question to, and get a reliable response. Not AI slop.A data scientist you can email. Not AI slop.
Upload a CSV, map your sequence and measured value, and get an Individuals control chart with 3-sigma limits, every Western Electric signal flagged, and a clear in-control verdict. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size, so sign up to analyze your full dataset.
Building your control chart...
Sent to . Inside: Individuals control chart with 3-sigma limits, flagged special-cause signals, a process summary, R code, and AI insights.
Analyze another fileThe measurements are ordered by the sequence column and plotted as an Individuals (I) chart. The center line is the process mean; the natural process limits are set at three sigma, where sigma is estimated from the average moving range (the mean absolute change between consecutive points, divided by 1.128). A practical subset of the Western Electric / Nelson rules then scans for special-cause signals: a point beyond the limits, nine points on one side of center, six points trending, and two of three points near a limit. If no rule fires, the process is in statistical control.
Use it whenever you have a stream of measurements in order — production runs, daily KPIs, sensor readings, test results — and want to know whether it is stable and predictable or whether something changed.
Not for judging whether output meets a specification (that needs spec limits and a capability study), and less reliable when the data is strongly autocorrelated or comes in natural subgroups.
Built for: Quality engineers, operations analysts, and anyone monitoring a process over time
Typical data source: A spreadsheet or CSV with an ordered sequence and a measured value per row
Any table with an ordering column and a measured value. For example, fill weights by sample:
Minimum 15 rows · Best with 25-500 ordered measurements
Standard-library analysis: an Individuals (I-MR) control chart for a sequence of measurements — the SPC / Six Sigma staple for telling a stable process apart from one throwing special-cause signals. Computes the center line, the 3-sigma natural process limits from the moving range, and runs a practical subset of the Western Electric / Nelson rules to flag out-of-control points. Works on any dataset: map a sequence column (date, batch, or sample order) and the measured value.
Every measurement in order against the center line and 3-sigma limits; colored points are the special-cause signals to investigate.
Which control rules fired and how many points each flagged — the specific patterns that mark an unstable process.
The process at a glance — mean, sigma, control limits, and whether it is in statistical control.
Plain-English interpretation of what the numbers mean, what's significant, and what to do next.
Is my process stable, or did something change?
Map a sequence column and your measured value. You get an Individuals control chart with the center line and 3-sigma natural limits, every special-cause signal flagged by the Western Electric rules, and a clear in-control or out-of-control verdict.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data: R analyses, interactive reports, AI insights, and PDF export.
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CympleData Scientist Send me your data and question, I’ll send you the analytics. ds@mcpanalytics.ai
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