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📦 Box Plot Analysis
Compare multiple groups at a glance: center, spread, outliers
Each line = one group (process / machine / supplier / batch…), several numbers after it are that group's readings. Start a line with a group name (e.g. "Machine A"); if a line has no name it is numbered automatically. Group sizes may differ. Which groups have shifted center / larger spread / outliers is obvious at a glance. Typical use: compare diameter spread between 3 suppliers, or compare the distribution shift after changing a process.
Paste data (one group per line, multiple readings within a line)
What does a box plot tell you?
· Each box: the middle line is the median (center), the box spans Q1~Q3 (the central 50%, reflecting spread), the whiskers extend to non-outlier extremes, ● red dots are outliers
· How to compare: if the boxes clearly "stagger" (one group's median well above/below another) → the groups may differ in center; if one box is obviously longer → that group has larger spread. Outliers point to sporadic process mistakes or special causes
· Box plots are for comparing distribution shapes across groups; to rigorously test "whether the group means are equal" → "One-Way ANOVA" (or the "t-test" tool for two groups). Spread comparison → "Levene's test"
· If there are only individual values of a single group (no grouping) → "I-MR / distribution check" is more appropriate
· How to compare: if the boxes clearly "stagger" (one group's median well above/below another) → the groups may differ in center; if one box is obviously longer → that group has larger spread. Outliers point to sporadic process mistakes or special causes
· Box plots are for comparing distribution shapes across groups; to rigorously test "whether the group means are equal" → "One-Way ANOVA" (or the "t-test" tool for two groups). Spread comparison → "Levene's test"
· If there are only individual values of a single group (no grouping) → "I-MR / distribution check" is more appropriate
About Box Plot Generator
Generate box plots from grouped data: median, quartiles, whiskers and outliers, multi-group comparison with AI interpretation.
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