About Kevin Gray

Kevin Gray is president of Cannon Gray, a marketing science and analytics consultancy.

Kevin Gray Posts (27)

  • How Not To Lie With Statistics - 11 Jan 2018
    Darrell Huff's classic How to Lie with Statistics is perhaps more relevant than ever. In this short article, I revisit this theme from some different angles.
  • Demystifying Data Science - 26 Dec 2017
    Marketing scientist Kevin Gray asks Dr. Randy Bartlett of Blue Sigma Analytics what Data Science really is and how it can help decision-makers.
  • Some Things to Remember About Memory - 14 Nov 2017
    A lot of the recent buzz about memory is old news.
  • Conjoint Analysis: A Primer - 01 Nov 2017
    Conjoint is another of those things everyone talks about but many are confused about…
  • Gold BlogWant to Become a Data Scientist? Read This Interview First - 13 Oct 2017
    There’s been a lot of hype about Data Science... and probably just as much confusion about it.
     
     
  • Statistical Mistakes Even Scientists Make - 03 Oct 2017
    Scientists are all experts in statistics, right? Wrong.
  • How To Lie With Numbers - 21 Sep 2017
    It takes less effort to lie without numbers, but there are now more numbers and more ways to lie with them than ever before. Poor Reverend Bayes, who understood the true meaning of "evidence".
  • Big Data or Big BS? - 07 Sep 2017
    Data and analysis of data have, in some form, been used to aid decision making since ancient times. So why, after all these centuries are data and analytics not more embedded in corporate decision making?
  • Vital Statistics You Never Learned… Because They’re Never Taught - 29 Aug 2017
    Marketing scientist Kevin Gray asks Professor Frank Harrell about some important things we often get wrong about statistics.
  • Causation: The Why Beneath The What - 18 Aug 2017
    A lot of marketing research is aimed at uncovering why consumers do what they do and not just predicting what they'll do next. Marketing scientist Kevin Gray asks Harvard Professor Tyler VanderWeele about causal analysis, arguably the next frontier in analytics.