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Graphical summary (descriptive statistics and normality), hypothesis tests (t, proportions, variances, Poisson, A × B comparison), power and sample size, chi-square (association and goodness of fit) and nonparametric tests (sign, Wilcoxon, Mann-Whitney, Kruskal-Wallis, Mood, Friedman and runs).
Paste one or several columns (machines, shifts, lots) and get, for each, the summary report with histogram and normal curve, boxplot, confidence intervals for the mean and median, Anderson-Darling test and full descriptive statistics, plus boxplots and a probability plot comparing the groups. Use it before computing capability, building control charts or comparing machines: it shows whether the data are reliable and normal.
Descriptives, normality, CICompare supplier A × B, old × new method, shift × shift or before × after: the page picks the test from the type of result, shows the difference with its confidence interval, the no-real-difference band, the power and how many more samples are needed, and translates it into parts and money per year. It also runs 1- and 2-sample and paired t-tests, 1 and 2 proportions, 1 and 2 variances and Poisson rates. Every result comes with charts and a plain-language explanation.
t, proportion, variance, A × BFind out how many parts, items or runs to measure before comparing suppliers, machines, shifts or methods: sample size for the desired power, power of a given sample or the smallest detectable difference, with power curves, a scenario table and sampling cost. It also plans ANOVA, factorials (DOE), equivalence and the margin of error for estimating a mean or a proportion.
How many parts to measurePaste a count table (press × shift, supplier × inspection) or the raw data and see whether there is an association, with expected counts, contributions, adjusted residuals, Cramér’s V and Fisher for 2×2; or test whether defect types follow historical proportions and whether defects per part follow the Poisson. Each chart comes with an explanation of where the difference lies.
Association, goodness of fit, FisherCompare medians without assuming normality: repair times by shift, bearing life from two suppliers, setup against the target, inserts tested on the same machines, and check whether a production sequence is random. With median CIs, ranks, tie adjustment and plots by group explained in plain language.
Medians, ranks, runsA histogram shows how the measurements of one characteristic are spread: where the center is, how much they vary and whether they fit within the specification limits. It is the first tool to understand a process before computing Cpk or changing settings. Paste measurements from Excel and get a histogram with automatic or adjustable bins, normal curve, mean and ±3s, specification limits with % out, a dot plot for small samples, overlaid, stacked or paneled groups, a plain-language reading of the shape and a frequency table.
Shape, bins, % outA box plot sums up many values in a single box and lets you compare several groups at once: which machine, shift or supplier has the highest level, which varies most and which parts stand out. Paste one or several columns (machines, shifts, suppliers) and get the box plot in vertical or horizontal orientation, with Minitab-method quartiles, whiskers to 1.5 × IQR, outliers labeled with value and row, the mean, individual points, a median-CI notch, ordering by median and specification limits.
Quartiles, outliers, groupsPaste measurements (single column, subgroups or ID) or enter mean and standard deviation: Cp, CPL, CPU, Cpk, Pp, Ppk, Cpm with 95% CI, observed and expected PPM, Z.Bench, control charts, Box-Cox, Johnson, Weibull and lognormal, and the payoff of reducing variation.
Cp, Cpk, PPM, sigma levelImportant notice: Indus Metrics tools produce estimates and pre-sizing results from the data you enter and from published engineering methods. They do not replace design, calculations or reports signed by a licensed professional engineer (PE), nor verification against the applicable codes, standards and regulations, such as OSHA rules and the ASME codes. Material and fuel properties vary: check manufacturer data or your own process analyses before deciding. By using this site you agree to the Terms of Use.
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