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