Measuring a small number of samples, and the 3v fallacy: Shedding light on confidence and error intervals

被引：31

作者：

Schmid, Hanspeter ^{[1
]}

Huber, Alex ^{[1
]}

机构：

[1] Institute of Microelectronics, University of Applied Sciences Norhtwestern Switzerland, Windisch

来源：

IEEE Solid-State Circuits Magazine | 2014年 / 6卷 / 02期

关键词：

Timing circuits;

D O I：

10.1109/MSSC.2014.2313714

中图分类号：

学科分类号：

摘要：

Many solid-state circuits papers today report the mean and the standard deviation of measurement results obtained from a small number of test chips and then compare them with numbers other authors obtained. Almost none of them discuss confidence intervals, ranges of values for that standard deviation within which the true value lies with a certain probability. Many implicitly assume that the range would contain all but 0.27% of chip samples to be expected in volume production. This is incorrect even if it is certain that the measured quantity is exactly normal distributed. © 2014 IEEE.

引用

页码：52 / 58

页数：6

共 10 条

[1]

Berendsen H.J.C., A Student's Guide to Data and Error Analysis, (2011)

[2]

Pertijs M.A.P., Makinwa K.A.A., Huijsing J.H., A CMOS smart temperature sensor with a 3σ inaccuracy of ±0.1°C from -55°C to 125°C, IEEE Journal of Solid-State Circuits, 40, 12, pp. 2805-2815, (2005)

[3]

Schmid H., Companion Web App to This Paper

[4]

Student's Tdistribution

[5]

Chi-squared Distribution

[6]

Thompson W.R., On confidence ranges for the median and other expectation distributions for populations of unknown distribution form, Ann. Math. Statist., 7, 3, pp. 122-128, (1936)

[7]

Parren Der Van J.L., Tables for distribution-free confidence limits for the median, Biometrika, 57, 3, pp. 613-617, (1970)

[8]

Jaynes E.T., Probability Theory: The Logic of Science, (2003)

[9]

Kernel Density Estimation

[10]

Efron B., Tibshirani R.J., An Introduction to the Bootstrap, (1998)

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