Measurement and Statistics : Data Quality

Open Access

Back to Basics: Eight Simple Steps

by Sharma, Mohit

Collecting data is a critical and important step in putting a project together. In experience reviewing projects, I have seen Black Belts often make mistakes in collecting data. This affects the overall result....

Open Access

Volviendo a los Fundamentos: Ocho sencillos pasos

by Sharma, Mohit

Collecting data is a critical and important step in putting a project together. In experience reviewing projects, I have seen Black Belts often make mistakes in collecting data. This affects the overall result....

3.4 per Million: Understanding the Data

by Breyfogle, Forrest W. III

At the end of business quarters, many people spend precious time and effort preparing to satisfy management’s need to know how the business is faring....

Open Access

Perspectives: Traversing a Data Jungle

by Vaidya, Jigish

The definition of data, simply put, is facts and statistics collected for reference or analysis. Even more important, however, is thinking about how to make data work for you....

Open Access

Breaking Down Barriers

by Liu, Shu

To leverage the benefits and prepare for the challenges big data present, quality professionals must change their mindset, get more data, upgrade their skills and expand their roles in the big data universe....

Follow the Fundamentals

by Snee, Ronald D. ; DeVeaux, Richard D.; Hoerl, Roger W.

New technology for acquiring, storing and processing data is being introduced at an ever-increasing pace. In 2012, the White House launched a national “Big Data Initiative.” According to IBM, 1.6 zettabytes of digital data are now available....

Measure for Measure: Into the Unknown

by Shah, Dilip

For estimation of measurement uncertainty, both Type A and B uncertainty contributors may need to be considered, depending on the parameter that is being estimated....

Open Access

Balancing Act

by Montgomery, Eda Ross; Neway, Justin

With common quality methods and standards in place, manufacturing organizations share a daunting challenge: an increased volume of electronic and paper-based data collected during process development and manufacturing....

Expert Answers: April 2013

by QP Staff

Root cause analysis tools ... Calibration data for a fee ......

Statistics Roundtable: Inquiry on Pedigree

by Snee, Ronald D., Hoerl, Roger W.

THE MEDIA FREQUENTLY report on examples of situations in which results from statistical studies are not reproducible. A recent article in the New York Times reported how a sophisticated study went wrong because of poor data quality....

Open Access

One Good Idea: Complicated Comparison

by Bower, Keith; Germansderfer, Abraham

Limited data availability complicates an assessment of whether two populations are comparable. A statistical tolerance interval (TI) can be used to set the comparability criteria....

Statistics Roundtable: More is Not Always Better

by Anderson-Cook, Christine M.

All other things being equal, if offered a choice between small or large sample sizes, the larger sample size is preferred. Or is it?...

3.4 per Million: Data Dependability

by Kubiak, T.M.

As quality or Six Sigma professionals, we have been taught to address the issue of data accuracy and integrity from the statistical viewpoint....

Statistics Roundtable: It's Not Always What You Say, But How You Say It

by Hare, Lynne

The Youden plot has proven extremely useful in the analysis and interpretation of data generated by interlaboratory studies. It’s always easy to understand and motivates others to take action if...

Open Access

Back to Basics: Data Collection Guidelines: the People Element

by Laman, Scott

Collecting high quality data is essential to the success of any project, process improvement or new product development....

Open Access

Column: Back to Basics: Collecting Data for Root Cause Analysis

by Rooney, James J.; Vanden Heuvel, Lee N.

Collecting Data for Root Cause Analysis by James J. Rooney and Lee N. Vanden Heuvel actual evidence derived from data gathering activities is the basis for all valid conclusions and recommendations from a root cause analysis. Management can analyze the ...

Column: Statistics Roundtable: Another Data Mining Tool

by Mason, Robert L.; Young, John C.

In this column, we introduce the use of a Hotelling's T2 statistic as a data mining tool for large and small data sets composed of many variables. We will show how the T2 statistic, based on a single p-dimensional observation vector (x1, x2, ..., xp),...

Reliability Analysis by Failure Mode

by Doganaksoy, Necip; Hahn, Gerald J.; Meeker, William Q.

Reliability improvement should be a major consideration when conducting product life data analysis. One method of determining the failure mode responsible for failure is to perform separate analyses for each mode and combine the results, as opposed to...

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