Data Analyst (with Dr. John Johnson)

The majority of information that you read in the newspaper, see on T.V., experience in your life, is wrong, misleading, or out of context. The important part of good data intuition is putting things in context.

Did you hear, studies say two cups of coffee a day will give you a healthier heart?!  I hear you, you can only drink coffee in the morning though.  Never fear, didn’t you know that studies show that two glasses of red wine a night are proven to make you live longer?!  I know, it’s the perfect one two punch!  If only there was a study that supported my love of unhealthy food, like, oh, I don’t know, that eating grilled cheese sandwiches will make you more likely to have sex.  This new world of studies is so great!  Just start the Blake Fletcher patented ‘Coffee, wine, grilled cheese’ diet and you’ll be banging your way to a longer life in no time!  (Please don’t actually do that or you’ll probably get an arrhythmia, alcoholism, and clogged arteries)  It seems like studies are coming out every day that say…whatever the heck they want to say, and that new ones are always contradicting old ones.  What does it all mean?  Can we even trust studies and data at all anymore?  Dr. John Johnson, data analyst extraordinaire and co-author of the new book Everydata, is here to help us sort through everything.

In economics and statistics, causation [vs. correlation] is a very very high bar to get over. However, as human beings, people love to look for patterns in their everyday life, so you’ve got to look out for that.
Always ask yourself, what are they measuring? Who are the people that are responding? What is the story that’s trying to be told? How tortured do the numbers seem? Those are the kinds of things that I call raising flags that sort of help people to make more sense of numbers.

Interview Contents

6:20 - The explosion of stats around us.
9:20 - Statistical literacy.
11:20 - Statistical bias and cherry picking data.
16:10 - Correlation vs. causation.
25:20 - Placebo and capturing the correct cause.
27:35 - The difficult of analyzing certain data and studies.
31:50 - Margin of error and p-values.
38:20 - Can we ever feel confident when analyzing data?
39:05 - The best ways to spot poor data.
40:20 - What people hire John for.
43:50 - Being discerning consumers of data.
44:50 - The work John did on NFL player safety.
47:40 - The future of data.
49:20 - Key takeaways from John’s book.


John's book EVERYDATA

John's website



Michelle & Jim Wortner

Janelle Swanson

Jimmy Seymour


Blake Fletcher

Livin it up!