Preparing For The Coming Flood… Of Statistical Malfeasance

Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance

Identifying & Understanding Statistics Problems

The nonstatistician cannot always recognize a statistical problem when he sees one.W. Edwards Deming

For business, the recent growth in fact-based decision making has provided a path to innovative new products and an escape for companies in disrupted industries.  Over the coming years, we should expect a corresponding growth in statistical malfeasance.  How large, you may well ask.  We can not be sure, even measuring today's statistical malfeasance is difficult.  In addition to market forces, an important ingredient in this flood is a number of misunderstandings about the purview of Statistics, statistical thinking, and the underlying statistical assumptions.

The key element for a successful (big) data analytics and data science future is statistical rigor and statistical thinking of humans.Diego Kuonen
The best protection from statistical malfeasance is to leverage three pillars for Best Statistical Practice: Statistical Qualifications, Diagnostics, & Review (QDR) (see 'A Practitioner's Guide To Business Analytics,' McGraw-Hill (2013), Chapters 7-9).  The better we understand statistics problems, the better we can identify the best Statistical Qualifications, interpret the right Statistical Diagnostics, and apply an appropriate Statistical Review.  We need to use Statistical Diagnostics to measure the accuracy and reliability of results.  Diagnostics are far more important for statistics problems, which do not have unique solutions in the way that we can mathematically deduce one answer.  We need Statistical Review to continuously improve decision making, data analysis, and data management.  Again, these three pillars are best facilitated using a savvy understanding of statistics problems.

Read Also:
Automated Predictive Analytics – What Could Possibly Go Wrong?

The article continues in the May/June 2015 issue of Analytics Magazine



Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance



Sentiment Analysis Symposium

off with code

Read Also:
Blog 8: Statistics Denial Myth #4, Rebranding Predictive Modeling

Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance



Data Analytics and Behavioural Science Applied to Retail and Consumer Markets

off with code

Read Also:
Solving Business Problems with Data Science
Read Also:
Understanding The Impact of Open Data Technology In The Nigerian Health Sector

Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance



AI, Machine Learning and Sentiment Analysis Applied to Finance

off with code

Read Also:
Blog 7: Statistics Denial Myth #3, Repackaging Statistics With Straddling Terms

Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance



Real Business Intelligence

off with code

Read Also:
Blog 8: Statistics Denial Myth #4, Rebranding Predictive Modeling
Read Also:
Solving Business Problems with Data Science

Randy Bartlett

Randy Bartlett, Ph.D. CAP® PSTAT® is a statistician/statistical data scientist with 20+ years of practice experience analyzing and reviewing data analysis; and leading business analytics teams.He designed 'A Practitioner’s Guide to Business Analytics' to be the foremost reference on how corporations can better implement business analytics and in this era of Big Data.

Preparing For The Coming Flood… Of Statistical Malfeasance



Advanced Analytics Forum

off with code

Read Also:
Blog 7: Statistics Denial Myth #3, Repackaging Statistics With Straddling Terms

Leave a Reply

Your email address will not be published. Required fields are marked *