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Upload your data and get a complete normality & outlier screening report. Free.
The practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
Standard-library analysis: before you run a t-test, ANOVA, or regression, check whether each numeric column is fit for those methods. For every column it reports the mean, median, spread, skewness and kurtosis, runs the Shapiro-Wilk normality test, counts outliers with the 1.5 and 3 times IQR rules plus a Grubbs test on the single most extreme value, and gives a clear parametric-versus-nonparametric recommendation. Works on any dataset: map the numeric columns you plan to test.
Interactive table visualization
Interactive table visualization
Interactive bar visualization
Plain-English reading of the results and what to do next.
Check whether a column is normal enough for a t-test or ANOVA
See our FAQ for pricing, privacy and how the analysis works.
MCP Analytics. Normality & Outlier Screening. Free tool. https://mcpanalytics.ai/free/standard_data_screening. Accessed [date you used it].
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