A useful star sign metaphor for the general concept of fitting models to data

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In “Explaining statistical methods to the terrified & disinterested: A focus on metaphors”, I discuss the usefulness of metaphors for explaining abstract statistical concepts to non-technical readers. This is an approach taken in my new SAS Press book, Business Statistics Made Easy in SAS®, since many readers of this level of book are non-technical, disinterested or downright frightened of statistics.

In this blog, I unpack one such metaphor for fitting mathematical models to data, which may be useful for instructors teaching similar material. This is taken directly from Chapter 11 of Business Statistics Made Easy in SAS®.

The star sign metaphor for fitting models to data

I like the metaphor of star constellations as a picture for data fitting. Think of the stars as data. Nothing in the stars is an exact pattern. But, sometime in history, some Greek turned around to his friend and went “Dude! Those stars over there look like a lion!” Take a look at this picture for the basic pattern of the stars of the constellation Leo.

Leo_1

The photo below shows a hypothetical picture of a lion laid over the stars – you may think of the picture as an exact perfect model of a lion. The stars do not follow the lion picture exactly, but perhaps they come close enough to give agreement that a lion is a good approximation of the pattern.

Leo_2

Your task would be to determine how closely the data (or stars) really fit to the picture of the lion. Plots and certain fit statistics would typically be available for this. If the data does not fit a lion, perhaps there is no shape, or perhaps some other shape will fit well (a dog? a car?). The final shape that fits may or may not be helpful to you – that would be another question, and is discussed in the next major step on interpretation.

Following up on this metaphor

I follow up on this metaphor in my book with more concrete examples of fitting a normal distribution to a single variable’s distribution and a linear line to a bivariate scatterplot.

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About Author

Gregory Lee

Research Director

Professor Gregory John Lee is currently the Research Director and an Associate Professor in Research Methodology and Decision Sciences at the AMBA-rated Wits Business School, Johannesburg, South Africa. He has authored books on HR Metrics, including his newest title, Business Statistics Made Easy in SAS. Lee focuses on issues in human resource management, notably HR metrics, in which he has established himself as a leading expert, and other areas such as training, employee turnover, and the employee-customer link. He has served in many capacities within the international academic field and has sat on the GMAC Advisory Council, the editorial board of the Journal of Organizational and Occupational Psychology, and he engages in frequent reviewing for many journals. In addition, Lee is a well-known consultant, writer, and speaker in the corporate and practical management arenas, notably in the area of HR metrics but extending to other areas such as human resources strategy and foresight.

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