Food for Thought

Statistical Modeling: A Primer (by Kevin Gray)

March 7, 2017

Interesting article by Kevin Gray at Cannon Gray (http://cannongray.com) Model means different things to different people and different things at different times. As I briefly explain in A Model’s Many Faces, I often find it helpful to classify models as conceptual, operational or statistical. In this post we’ll have a closer look at the last of these, statistical models. First, it’s critical to understand that statistical models are simplified representations of reality and, to paraphrase the famous words of statistician George Box, they’re all wrong but some of them [READ MORE]

Skepticism in Social Media

June 15, 2016

I was talking this morning with someone about which blogs that review products and/or services are the most popular around my part of the world – Asia. I consulted Google Search but could not come up with an answer. I did however come across a recent report (June 25, 2012) by Kristen Sala, Senior Manager, Electronic Media at Cision (a public relations software and media tools firm) that lists the Top 50 independent “Product Review Blogs” in North America. Mama-B Blog is first, followed by Computer Audiophile, and 48 others.  Still, I could not find much information [READ MORE]

Is my Likert-scale data fit for parametric statistical procedures?

April 8, 2016

We’re all very familiar with the “Likert-scale” but do we know that a true Likert-scale consists not of a single item, but of several items which under the right conditions – i.e. subjected to an assessment of its reliability (e.g. intercorrelations between all pairs of items) and validity (e.g. convergent, discriminant, construct etc.) can be summed into a single score. The Likert-scale is a unidimensional scaling method (so it measures a one-dimensional construct), is bipolar, and in its purest form consists of only 5 scale points, though often we refer to a [READ MORE]

Two research fallacies

December 9, 2015

The Research Methods Knowledge Base website reminds us researchers (and readers of research findings) of the “Two Research Fallacies”.    “A fallacy is an error in reasoning, usually based on mistaken assumptions”.   The two most serious research fallacies discussed in this article are the “ecological fallacy” and the “exception fallacy”   “The ecological fallacy occurs when you make conclusions about individuals based only on analyses of group data”.  For example, if the average income of a group of people is $60,000, we [READ MORE]

Marketing research and theory

November 12, 2015

  I was inspired by the article (or open letter) written by Terry H. Grapentine and R. Kenneth Teas entitled “From Information to Theory: it’s time for a new definition of marketing research” which appears on the AMA’s website, marketingpower.com (accessed October 2012).  The authors debate the importance of theory in marketing research and urge for the rightful place of “theory” and the “creation of knowledge” in the American Marketing Association’s definition of marketing research.    They propose a new definition of marketing [READ MORE]

Measuring importance

April 14, 2015

Lets have a quick review of how we measure importance e.g. of attributes in purchase decisions or in customer satisfaction, etc.   Traditionally we looked at stated importance but generally we give preference to derived importance.  So we’ve been taught.   Stated importance can be divided into the constrained methods (e.g. a 5-point rating scale, constant sum methods, Q-sort, and rank order) and unconstrained methods which are unbounded rating scales and open-ended questions.    On the other (better) hand, derived importance can be established via correlation-based methods such as [READ MORE]