Why measures of variability matter: Average age of death in The Olden Days

Alright, this is a 30-second long example for a) bimodal distributions and b) why measures of variability matter when we are trying to understand a mean.

And that mean is...AGE OF DEATH.

A GIF of Wednesday Addams trying to smile. And failing.

My inspiration for this tweet is:

Gullett refers here to the commonly held belief that if the mean life span Back In The Day was 45, or thereabout, everyone was dying around 45. NOT SO.

Why?

OK. Angelle is invited to my parties. She would tell us how many humans didn't survive childhood. AND THEN...a bunch of people would croak around 50. 

*Let's take a moment and send some good thoughts and gratitude to the memories of Jonas Salk, Edward Jenner, and Alexander Flemming.*

Yet another Twitterer then shared this data visualization to demonstrate how mortality has changed over time. 

When I shared this in class, I threw these Tweets up on a PPT slide. Again, it shows a roughly bimodal distribution, with death increasing in childhood and 50. It also demonstrates why we need to discuss the variability in a data set, not just the midpoint. 

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