Explaining statistical methods to the terrified & disinterested: pictures & diagrams

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In a previous blog I suggested that many readers in many applied areas are reading statistics texts under duress for a course or project, and are in truth somewhere between disinterested and terrified. In my new SAS Press book Business Statistics Made Easy in SAS® I make use of various intuitive explanatory techniques, including:

  1. Metaphors
  2. Pictures & diagrams
  3. Organizational cases / vignettes
  4. Storytelling

In this blog, I explore the use of pictures & diagrams in more detail.

A picture tells a thousand words

In Business Statistics Made Easy in SAS® a key philosophy was to use explanatory diagrams and pictures wherever possible. Feedback from students consistently supports this technique. The following are some common types.

Flowcharts of technique steps

From experience teaching MBA and other classes, flowcharts of an overall technique decision process are ‘teaching gold.’ These are used in many statistical texts, yet I believe they are still not used enough.

See the figure below for an example from Business Statistics Made Easy in SAS®, in which I summarize steps for linear regression. Without the flowchart, the detailed 50+ page chapter would be far harder to assimilate, organize, and remember.

Statistics Picture_1

Explanatory pictures of specific concepts

When using specific illustrations, the occasional pictorial illustration can really help. See <Fig 2> for an illustration from Business Statistics Made Easy in SAS®. I find that pictures that tell a story are often effective. I’ll have more on storytelling in a later blog.

SAS code, output, etc.

Here I favor annotating screenshots from SAS with helpful, short explanations in text, using arrows and the like to point out the key areas of interest in the screenshot. See below for an example from Business Statistics Made Easy in SAS®, in which I explain the tTest.

Are my pictures useful?

How about this for a radical test of the usefulness of your figures: could you use only the pictures in a series of projection slides and still be able to talk around the entire chapter / section / concept?

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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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5 Comments

  1. On the webpage
    http://blogs.sas.com/content/sastraining/2016/02/18/explaining-statistical-methods-to-the-terrified-disinterested/?EMAIL=ian.shannon%40environment.nsw.gov.au&appid=49701

    There is a slipup in the wording of the explaination.


    If we can say we are 99% confident that the true statistic lies close to 30 ...

    In this case (and a few other places as well) the words should have been "true value" not "true statistic".

    A statistic is a calculation from a sample and (of course) will vary with different samples being taken. The true value is stuck on one value.

    The distinction is important especially if the aim to to get new people to get into statistics!

    Ian

        • Gregory,

          Thanks for changing, however I did say (and a few other places as well). Just above in the section starting Accuracy: you also use true statistic. I really like Rick's suggestion of using true population value.

          Ian

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