Your quick reference for center, spread, shape, plots, Excel, and “what to do next.” Includes a paste-n-compute mini-calculator.
max − minQ3 − Q1 (robust)SD / mean (unitless)< Q1 − 1.5·IQR or > Q3 + 1.5·IQRBefore modeling/regression: scan histograms/box plots, run a scatter of Y vs X, check normality and possible transforms.
Use \(n-1\) degrees of freedom for samples.
\(k\) = number of bins, \(w\) = bin width.
Shape Skew, multimodality; compare bin rules.
Tip Start with √n, then try FD for fine structure.
Compare Median shift (center) & IQR (spread).
Outliers 1.5·IQR rule for flags.
Great for small n; preserves individual values and shows shape.
Y vs X trend, form, outliers. Don’t connect dots unless X is time.
Detect shifts/drift/cycles. Use before relying on a histogram.
≈ straight line → plausible normal. S-curve/ends off → skew/heavy tails.
Assume your data are in B2:B101. Replace ranges as needed.
| Task | Excel | 
|---|---|
| Mean | =AVERAGE(B2:B101) | 
| Median | =MEDIAN(B2:B101) | 
| SD (sample) | =STDEV.S(B2:B101) | 
| Min / Max | =MIN(B2:B101)/=MAX(B2:B101) | 
| Q1 / Q3 (EXC) | =QUARTILE.EXC(B2:B101,1)/=QUARTILE.EXC(...,3) | 
| IQR | =QUARTILE.EXC(...,3)-QUARTILE.EXC(...,1) | 
| z-score for B2 | =(B2-$F$2)/$F$3(F2=mean, F3=SD) | 
| Correlation (X,Y) | =CORREL(C2:C101, D2:D101) | 
| Chart | Steps | 
|---|---|
| Histogram | Insert → Statistic Chart → Histogram; try different bin widths. | 
| Box & Whisker | Insert → Box & Whisker; shows median/IQR/outliers. | 
| Scatter | Insert → Scatter (no lines); Y on vertical, X on horizontal. | 
| Q–Q (manual) | Sort, compute theoretical normal quantiles via =NORM.S.INV(P), then scatter. | 
Paste numbers (one per line or comma-separated). We’ll compute n, mean, median, SD, min, max, Q1, Q3, IQR, and \( |z|>2 \) count. Data stay in your browser.
| n | — | 
|---|---|
| Mean | — | 
| Median | — | 
| SD (s) | — | 
| Min / Max | — | 
| Q1 / Q3 | — | 
| IQR | — | 
| |z| > 2 (count) | — | 
| Bin Suggestions | — | 
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n−1 for variance).