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Fighting Crime With Statistics
Taking advantage of ‘natural experiments,’ researchers analyze data to look at what works
Watch Out for the Big Data Steamroller
The most seductive waste of all
What Is the Probability That Your Process Is Predictable?
How to compute a p-value for your process behavior chart
Control Charts: Keep It Simple
Myth, misunderstanding, and bad teaching have lead to the belief control charts are hard. They aren't.
Metrics: The Good, the Bad, and the Ugly
Part three: the ugly
Model-Based Definition: A Seven-Point Summary
Interoperability is key to avoiding the manual steps and hand-offs that Industry 4.0 hopes to eliminate
Reverse-Engineer Your Experiments
Be deliberate about the sample size you use
Why Simulation Is the Future of Uncertainty Evaluation
A model for complex measurements
Why Did Shewhart Place a Premium on Time Order Sequence?
Avoid the unnecessary waste of being misled
Beyond the Hype: Machine Learning for Manufacturing Performance
As a tool, machine learning can accelerate insights in data for more efficient manufacturing and drive innovation
Which Chart to Use?
Individual values or averages?
Getting Started with Process Validation Tools
Passing the three FDA stage goals
Metrics: The Good, the Bad, and the Ugly
Part two: the bad
Data Snooping Part 4
How’s that classification scheme working out for you?
d2: More Than Just a Control Chart Constant
We owe a debt of gratitude to Tippett and other pioneers who put ‘engineering’ into quality engineering.
How to Choose the Best Regression Model
There’s a Goldilocks balance with the number of predictors to include
Inside Quality Digest Live for Oct. 26, 2018
What kind of review would you give the Bates Motel?
Metrics: The Good, the Bad, and the Ugly
Part one: the good
Inside Quality Digest Live for Oct. 12, 2018
All about data—and genomes
Applying the Procedures of MIL-STD-105 to Imaginary Limits
Procedure doesn’t allow nonconforming units in the sample, has superior detection capabilities

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