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R For Business Purposes - An Example From Market Research

In marketing research and business analysis, there is often the requirement to compute the 'relative importance' of underpinning predictor attributes on some overall criterion measure (such as Overall Satisfaction).

This is often done using Regression, either by looking at the relative size of coefficients for each predictor, or by looking at the relative contribution of each predictor to R-squared.

However, even assuming that R-squared is a ‘useful’ metric (debateable), this approach is often compromised by the presence of collinearity.  The aim of the presentation is to illustrate this dilemma with a small number of test data sets, and suggest a potential way out, using one of the analytical approaches that were originally been developed for the data mining field.

Those looking for a detailed exposition of fiendishly clever R code will be disappointed.  Those who are interested in how selected pieces of a massively capable language such as R can be utilised for business purposes, without the need to write, nor to understand, reams of script will hopefully find the presentation of value.

Speaker’s background:  Scott MacLean

Scott is by no means an R expert, but rather a sometime user, currently mainly via Graham Williams’ Rattlepackage[1].  He also uses the Q package[2] extensively (which is not R-based) and which he loves, although in terms of usefulness, he believes that Rattle currently comes a not-too-distant second!  [As an aside, it is pleasing to note that both packages were developed, and continue to be supported, largely by Australian-based teams.]

Scott’s work experience is predominantly in the market research industry (30+ years), including nine years with AGB:McNair/AC Nielsen, seven years with Research International (Melbourne, Frankfurt and London) as Marketing Science/Research Director and two years with Lewers Research (Melbourne) as Head of Advanced Analytics.

For the past four years, he has been Principal of Nulink Analytics, specialising in quantitative input for business decisions. 

Scott has advanced level qualifications in statistical analysis and modelling:

Bachelor of Science (Hons) - mathematical and survey statistics, Monash University

Master of Applied Science  - transportation planning and modelling, Univ. of Melbourne

He is an elected Fellow of the Australian Marketing and Social Research Society (AMSRS), and has recently presented full-day workshops for AMSRS in Choice Modelling, and Segmentation using Latent Class Analysis.


[1] http://rattle.togaware.com/

[2] http://q-researchsoftware.com/

Join or login to comment.

  • Scott M.

    Sorry, there is no video... There was noone at this meeting to record one.

    April 5, 2014

  • Abiodun M.

    Video upload of the presentation will be appreciated.Thank u

    April 5, 2014

  • Khang V.

    Any video for this meetup?

    February 23, 2014

  • James N.

    Really appreciate Scott making to effort to prepare and deliver this presentation. The insights into the rattle package were very helpful and inspired ideas. I was hoping that the bulk of the presentation would be about how Scott typically uses rattle (or R) in his work and the value that it brings. That said, I have 100% respect for Scott volunteering to take the time and effort give us this presentation.

    February 20, 2014

  • Andrew W.

    Very practical and interesting talk by Scott MacLean. He has a nice sense of humour and a down-to-earth style.

    February 20, 2014

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