Tools › Statistics › Descriptive and Outliers › Data Summary and Outliers › Example

NIST e-Handbook 1.4.2.8.3: heat flow meter calibration data (ZARR13), summary and tests

ToolData Summary and Outliers
SourceNIST/SEMATECH (2012). "Heat Flow Meter 1: Quantitative Output and Interpretation." e-Handbook of Statistical Methods. Section 1.4.2.8.3, data set ZARR13.DAT.
LevelUndergraduate

Problem

Zarr's 195 calibration measurements of a heat flow meter (9.206343, 9.299992, 9.277895, …) are to be summarized: location and spread with their confidence intervals, lag-1 autocorrelation, a normality test and a check for an outlier at the 5 % level.

Inputs to Enter

  • Column calibration, 195 values (loaded by default; a second illustrative column sample_b with a planted 14.9 is also loaded)
  • Outlier level α = 0.05, max outliers 10
Open the Data Summary and Outliers tool (loaded with this example)

Answers

  • Mean 9.261460, standard deviation 0.022789, 95 % interval of the SD 0.02073 to 0.025307; lag-1 autocorrelation 0.280579
  • Grubbs G = 2.918673 (page; exact 2.918638) at row 46 (9.327973) against the critical value 3.597898, no outlier; the page labels the critical value one-tailed but it is the α/(2N) value
  • Anderson–Darling adjusted A² = 0.129; normal PPCC 0.999 (the 0.996 of 1.4.2.8.3 is a stale figure, 1.4.2.8.4 prints 0.999); Shapiro–Wilk W 0.99827, p 0.9992
  • Tukey inner fences 9.2029 and 9.3191; generalized ESD R1 = 2.9186 = Grubbs G, λ1 = 3.5979

Notes

The tool's default data set is this example; press Submit. Dixon's test is refused at n = 195. The chi-square critical value 7.815 and the t intervals follow the page.

More Examples for This Tool