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Quality Digest Columns by Donald J. Wheeler
2022
392. Jan 22 How Can Sum of Skewed Variables Be Normally Distributed?
394. Feb 22 The Analysis of Observational Data
395. Mar 22 The Analysis of Experimental Data
396. Apr 22 How Acceptance Sampling Works
398. May 22 How Can a Control Chart Work Without a Distribution?
2021
382. Mar 21 Tightened 100% Inspection
383. May 21 When to Use Tightened Inspection
384. Jun 21 More About the P/T Ratio
385. Jul 21 Problems with AIAG Gauge R&R Study
386. Aug 21 What Are Variance and Standard Deviation
387. Sep 21 What Are Skewness & Kurtosis
389. Oct 21 So You Want to Use a p-Chart?
390. Nov 21 So What is the Fraction Nonconforming?
391. Dec 21 Torturing the Data
2020
357. Dec.19 Short Run SPC Part One
358. Jan.20 Short Run SPC Part Two
359. Feb.20 Short Run SPC Part Three
361. Mar 20 Short Run SPC Part Four
368. May.20 Setting the Process Aim Part One
369. Jun.20 Setting the Process Aim Part Two
370. Jul.20 Expanded Tables for the Analysis of Mean Moving Ranges
373. Aug.20 Process Behavior Charts and Covid-19
375. Sep.20 The Progression of Covid-19 Within the U.S.
376. Oct.20 The Road to One Million
377. Nov.20 The Global Standard Deviation Statistic
378. Dec.20 Some Outlier Tests: Part One
379. Jan.21 Some Outlier Tests: Part Two
2019
343. Jan.19 What is the Probability Your Process is Predictable?
344. Feb.19 Problems with Bubble Plots
345. Mar.19 The Keys to Quality Assurance
346. Apr.19 When Are Instruments Equivalent? Part One
348. May.19 When Are Instruments Equivalent? Part Two
349. Jun.19 When Are Instruments Equivalent? Part Three
351. Jul.19 Six Analysis of Means Techniques
353. Aug.19 Avoiding Bias Correction Confusion
354. Sep.19 The Normality Myth
355. Oct.19 The Ability to Detect Signals
356. Nov.19 Phase Two Charts and Their Probability Limits
2018
326. Jan.18 Honest Precision to Tolerance Ratios
327. Feb.18 Is Last Digit Really Significant
328. Mar.18 The Empirical Rule
330. Apr.18 Is There an Empirical Rule for Prob. Models
331. May.18 The Think System for Improvement
332. Jun.18 Invisible Probability Models
334. Jul.18 Enumerative and Analytic Studies
335. Aug.18 Data Snooping Part One
336. Sep.18 Data Snooping Part Two
337. Oct.18 Data Snooping Part Three
338. Nov.18 Data Snooping Part Four
341. Dec.18 Which Chart to Use?
2017
304. Jan.17 Destructive Measurements
307. Feb.17 Imperfect Data
309. Mar.17 Three Way Chart
312. Apr.17 An F Test for 21st Century
314. May.17 More Capability Confusion
315. Jun.17 Using Less Than Perfect Data
317. Jul.17 History of XmR Chart
319. Aug.17 Autocorrelated Data
320. Sep.17 ANOX Test for Homogeneity
322. Oct.17 Using Extra Detection Rules
323. Nov.17 Sustaining Economic Operation
325. Dec.17 Capability Ratios Vary
2016
289. Jan.16 Statistical Tolerance Intervals
290. Feb.16 The Levey-Jennings Chart
291. Mar.16 Statistics 101 and Data Analysis
293. Apr.16 Useful Histograms
294. May.16 Optimization and Experimentation
295. Jun.16 Process Behavior Charts as Report Cards
296. Jul.16 Process Monitor Charts
284. Aug.16 Process Trial Charts
298. Sep.16 Homogeneity Charts
299. Oct.16 Input & Outcome Charts and EFAST Studies
300. Nov.16 The Locomotive of Continual Improvement
302. Dec.16 The Calibration of Measurement Systems
2015
277. Jan.15 Process Behavior Charts for Non-Normal Data: Part One
278. Feb.15 Process Behavior Charts for Non-Normal Data: Part Two
279. Mar.15 Probability Limits
280. Apr.15 Numerical Jabberwocky
281. May.15 The Parts Per Million Problem
282. Jun.15 Rational Subrouping
283. Jul.15 Rational Sampling
284. Aug.15 Properties of Probability Models: Part One
285. Sep.15 Properties of Probability Models: Part Two
286. Oct.15 Properties of Probability Models: Part Three
287. Nov.15 Shewhart and the Probability Approach
288. Dec.15 The Secret Foundation of Statistical Inference
2014
263. Jan 14 The Analysis of Experimental Data
265. Feb 14 Why Use Ranges?
266. Mar 14 Statistics and SPC
267. Apr 14 The Data-Free Graph
269. May 14 What Are Good Measurements?
270. Jun 14 What Is an Alpha-Level?
271. Jul 14 The Truth About Acceptance Sampling: Part One
272. Aug 14 The Truth About Acceptance Sampling: Part Two
273. Sep 14 A Problem with Outlier Tests
274. Oct 14 Don’t We Need To Remove Outliers?
275. Nov 14 Obey Gravity
276. Dec 14 A Tale of Two Comparisons
2013
251. Jan 13 But the Limits Are Too Wide!
252. Feb 13 The Secret of Process Adjustment
253. Mar 13 Right and Wrong Ways to Use Specifications
254. Apr 13 Consistency Charts
255. May 13 Contra Two Sigma
256. Jun 13 Why We Keep Having 100-Year FLoods
257. Jul 13 The Problem of Long-Term Capability
258. Aug 13 Beware the Tukey Control Chart
259. Sep 13 More to Beware About Tukey Control Charts
260. Oct 13 Separating the Signals from the Noise
261. Nov 13 Should the residuals be Normal?
262. Dec 13 Gauge R&R Methods Compared
2012
237. Jan.12 Lies, Damned Lies, and Teens Who Smoke While Driving
239. Feb.12 If It Ain't Broke…
240. Mar.12 Exact Answers to the Wrong Questions
241. Apr.12 When Should We Compute New Limits?
242. May.12 When Do We Use Subgrouped Data?
243. Jun.12 Analysis Using Few Data; Part One
244. Jul.12 What Is the Precision to Tolerance Ratio?
245. Aug.12 What is Leptokurtophobia?
246. Sep.12 What They Forgot to Tell You About the Normal Distribution
247. Oct.12 The Heavy-Tailed Normal
249. Nov.12 Analysis Using Few Data; Part Two
250. Dec.12 What Makes the XmR Chart Work?
2011
223. Jan.11 Problems with Gauge R&R Studies
224. Feb.11 A Better Way to Do R&R Studies
225. Mar.11 Three Questions for Success
226. Apr.11 How Measurement Error Affects the Four Ways We Use Data
227. May.11 100% Inspection and Measurement Error
228. Jun.11 Estimating the Fraction Nonconforming
230. Jul.11 Problems with Risk Priority Numbers
231. Aug.11 Problems with Skewness and Kurtosis
232. Sep.11 Myths About Process Behavior Charts
233. Oct.11 What About p-Charts?
234. Nov.11 Working with Rare Events
235. Dec.11 What is Chunky Data?
2010
205. Jan.10 The Right and Wrong Ways of Computing Limits
206. Feb.10 Individual Charts Done Right and Wrong
207. Mar.10 Scaling Factors for Process Behavior Charts
208. Apr.10 The Imaginary Theorem of Large Samples
209. May.10 Two Routes to Process Improvement
210. Jun.10 Is the Part in Spec?
213. Jul.10 Where Do Manufacturing Specifications Come From?
215. Aug.10 The Effective Cost of Production and Use
216. Sep.10 The Gaps between Performance and Potential
217. Oct.10 What Is the Zone of Economic Production?
220. Nov.10 Are You Sure We Don’t Need Normally Distributed Data?
222. Dec.10 The Intraclass Correlation Coefficient
2009
193. Feb.09 First, Look at the Data
194. Mar.09 Models Do Not Generate Your Data
195. Apr.09 No Data Have Meaning without Context
197. May.09 All Outliers Are Evidence!
198. Jun.09 Don’t the Outliers Distort the Limits?
199. Jul.09 Good Limits from Bad Data
200. Aug.09 Do You Have Leptokurtophobia?
201. Sep.09 Transforming the Data Can Be Fatal to Your Analysis
202. Oct.09 Avoiding Statistical Jabberwocky
203. Nov.09 Two Definitions of Trouble
204. Dec.09 The Four Questions of Data Analysis