Library

Newsletter Archive - full copies of past Division newsletters

Statistics Body of Knowledge - our library content below focuses on the topics in this listing.

Webinars

Applied Problem Solving and Research Using Statistical Methods with NIST Examples

by Adam L. Pinter

Workshop slides given by Dr. Adam Pintar of NIST to the Saskatchewan Section on September, 2016...

  • Filetype: pdf
  • Publish date: 2016-12
  • Keywords:DOE,NIST

Big Data Terminology—Key to Predictive Analytics Success

by Mark E. Johnson Dept. of Statistics, Univ. Cent. Florida

With all of the hype surrounding Big Data, Business Intelligence, and Predictive Analytics (with the Statistics stepchild lurking in the background), quality managers and engineers who wish to get involved in the area may be quickly dismayed by the terminology in use by the various participants. Singular concepts may have multiple names depending on the discipline or problem origin (business analytics, machine learning, neural networks, nonlinear regression, artificial intelligence, and so forth). Hence, there is a pressing need to develop a coherent and comprehensive standardized vocabulary. Subcommittee One of ISO TC69 is currently developing such a terminology standard to reside in the ISO 3534 series. In addition to the technical statistical-type terms, it could also include a discussion of some of the software facilities in use in dealing with massive data sets (HADOOP, Tableau, etc.). A benefit of this future standard is to shorten the learning curve for a Big Data hopeful. This paper des

  • Filetype: pdf
  • Publish date: 2016-10
  • Keywords:Big Data, Business Intelligence, and Predictive Analytics

Agile Teams: A Look at Agile Project Management Methods

by L. Allison Jones-Farmer and Timothy C. Krehbiel

A discussion of agile project management including scrum methodology. We see tremendous value that can be gained by the use of Agile methods along with existing project management frameworks. Although Agile lacks a systems focus, the Agile principles apply directly to managing smaller projects within enterprise-level initiatives. Analytics and data science projects are often exploratory in nature, require cross-functional teams to work together, and the scope is often developed through team discovery. Thus, we see Agile methods as particularly suited to moving analytics and data science projects forward, preventing backlogs and roadblocks that can occur due to uncertainty and poor communication

  • Filetype: pdf
  • Publish date: 2016-10
  • Keywords:Big Data, Business Intelligence, and Predictive Analytics

Scientific Method

The Generation of Knowledge and Quality

by Box, George;

A reprint of Dr. George E.P. Box’s "Scientific Method: The Generation of Knowledge and Quality", that explains how the concept of continuous improvement is a fundamental part of the scientific process!..

  • Filetype: pdf
  • Publish date: 2016-03
  • Keywords:Scientific method, quality improvement, inductive-deductive learning

Using the Fisher’s Exact Test to Determine Differences in Response Patterns

by Cudney, Elizabeth A.;

Fisher’s exact test is more appropriate than the chi-squared test of independence when the sample frequencies are low in categorical data...

  • Filetype: pdf
  • Publish date: 2016-02
  • Keywords:Fisher’s exact test, Likert scale, survey data, Chi-squared test

Youden Address

Perfect Makes Practice

by Brenneman, William A.;

Youden Address “Perfect Makes Practice” by Dr. William Brenneman, 2015 Youden honoree...

  • Filetype: pdf
  • Publish date: 2016-02
  • Keywords:Youden, Collaboration, Research

The Hype, myth, and reality of Data Science and Data Scientists

Featured Article from the October 2015 Statistics Digest

by Gutman, Alex J.;

Is Data Science the next big thing or an over-hyped idea that will fail to deliver any value? This paper is full of interesting and informativ..

  • Filetype: pdf
  • Publish date: 2015-10
  • Keywords:Data Science, Data Scientists, Predictive Analytics, Big Data

The Promise and Problems of the P-Value

Mini Paper from the October 2015 Statistics Digest

by Frost, Jim;

This Mini-Paper will help you to understand p-values in a more intuitive way and to avoid a very common misinterpretation that can cost you money and credibility. It will discuss how p-values and the null..

  • Filetype: pdf
  • Publish date: 2015-10
  • Keywords:P-Value, Hypothesis Testing, Significance Levels

Predictive Analysis of System Capability

Mini Paper from the June 2015 Statistics Digest

by Erik W. Smith

This Mini-Paper builds on the concepts of gage reproducibility and repeatability studies and analysis of variance, while expanding to include families of systems and moving from a reactive application to one that is predictive and proactive in nature.

  • Filetype: pdf
  • Publish date: 2015-07
  • Keywords:Capability Study, Measurements system Analysis, Gage R&R

Statistical Engineering and Tearing Down the Silos of Quality Engineering

Mini Paper from the February 2015 Statistics Digest

by Geoff Vining

This Mini-Paper emphasizes that Statistical Engineering only can succeed if we “blow up the silos” that separate the important quality engineering tools. Only true cross-disciplinary approaches can solve large, unstructured, complex problems, which is the key to the tactical approaches necessary for Statistical Engineering. It is bringing together the various tools in a coherent fashion that we can provide insights to solving classes of problems.

  • Filetype: pdf
  • Publish date: 2015-03
  • Keywords:Statistical Engineering, Six Sigma, ASQ’s Technical Communities Council

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