Six Sigma statistical tools for the complete DMAIC cycle Control charts, process capability with sigma level, Pareto analysis, hypothesis testing, and regression — every statistical tool a DMAIC project requires, from Measure through Control, in a single package.
Try free for 15 days — no credit card required
Trusted by 75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide — for over 30 years.
The full DMAIC toolkit in one package
Measure with control charts and capability indices. Analyse with Pareto and hypothesis tests. Improve with regression models. Control with ongoing SPC monitoring. No gaps to fill with secondary tools, no data transfer between applications.
Sigma level from your data
Cp, Cpk, Pp, Ppk, Cpm, Z-benchmark, and sigma level calculated from your process data — not estimated from a table. Separate capability and performance indices so you can distinguish what the process can achieve from what it actually delivers.
Results the whole team can share
All charts, analyses, and reports stay in Excel workbooks. Anyone in the organisation can open the results — management, finance, auditors, customers — without requiring a separate licence or proprietary viewer.
Six Sigma projects live or die on the quality of the statistical analysis at each stage of DMAIC. The Measure phase needs reliable control charts to establish whether the process is stable, and capability indices to quantify current performance against the specification. The Analyse phase needs Pareto analysis to identify the vital few causes, and proper hypothesis tests and regression to distinguish real root causes from coincidence. The Improve phase needs models that quantify the effect of changes and confirm the improvement is statistically significant — not just a difference that looks good on a chart. The Control phase needs ongoing monitoring that detects deterioration before it reaches the customer.
Most teams end up piecing this together from multiple tools — one for control charts, another for hypothesis tests, a spreadsheet for Pareto. Each tool has its own interface and its own output format. The practitioner spends time transferring data and reconstructing results rather than running the project. And when only one or two people in the organisation have licences for the dedicated tool, improvement projects stall waiting for the specialist to run the numbers.
Analyse-it covers the complete DMAIC statistical toolkit inside Excel. Shewhart variable and attribute control charts with WECO, Nelson, and Montgomery detection rules. CUSUM and EWMA for detecting small sustained shifts. Process capability with Cp, Cpk, Pp, Ppk, Cpm, Z-benchmark, sigma level, and nonconforming unit estimation — with Box-Cox transformations for non-normal data. Pareto analysis with one-way and two-way comparative charts. Hypothesis tests including t-tests, ANOVA, Welch's ANOVA, and non-parametric alternatives. Regression and ANCOVA with full diagnostics. All of it producing results in Excel workbooks that anyone in the organisation can open.
75,000 professionals at leading companies, hospitals, and laboratories worldwide have relied on Analyse-it for over 30 years.
What's included
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Establish baseline and monitor stability — Measure and Control
Shewhart variable charts (Xbar-R, Xbar-S, I-MR), attribute charts (p, np, c, u), and time-weighted CUSUM, EWMA, and UWMA charts. WECO, Nelson, and Montgomery detection rules. Phases for before-and-after comparison. Stratification by operator, shift, or machine. See control chart details.
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Quantify capability and sigma level — Measure and Control
Cp, Cpl, Cpu, Cpk, Cpm, Pp, Ppl, Ppu, Ppk, Z-benchmark, sigma level, and nonconforming unit estimation — all with confidence intervals. Box-Cox and other transformations for non-normal data. Histogram with specification limits and Q-Q plot. See capability analysis details.
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Identify the vital few causes — Analyse
One-way and two-way comparative Pareto charts. Break defect categories down by operator, shift, machine, or product line. Merge, reorder, and colour bars to focus improvement effort on the problems that matter most. See Pareto analysis details.
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Confirm root causes statistically — Analyse and Improve
t-tests, ANOVA, Welch's ANOVA, and non-parametric alternatives for comparing groups. Chi-square and Fisher exact tests for categorical data. Multiple comparison procedures including Tukey-Kramer, Dunnett, and Hsu. Statistical proof that a root cause is real, not coincidence.
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Model relationships and quantify improvements — Improve
Simple and multiple linear regression, polynomial regression, ANOVA and ANCOVA with interactions. Full residual diagnostics, leverage plots, and influence analysis. Quantify the effect of a change and confirm it is statistically significant.
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Part of the QC and Improvement edition
Every tool listed above is included in the QC and Improvement edition — the complete DMAIC statistical workflow in one package, inside Excel, at a fraction of the cost of dedicated Six Sigma tools.
Trusted by 75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide — for over 30 years.
Try free for 15 days — no credit card required
