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Thursday, August 27, 2020

Millennials: Yes, this was predicted.

I guess I'm developing a habit of an annual post about millennials. My first was in October 2018 and my second was September 2019

In the first post, I talked about my personal experience with different generations of students and linked to an article about millennials. In the second, I didn't say as much and linked to another article.

The overall message was - millennials aren't wildly different than prior generations.

Well here's another article about millennials. Since it's in the Wall Street Journal, it might be behind a paywall. So here's the main point: millennials - who were supposedly going to reject traditional family housing and completely change urban living - are driving the 2020 housing market.

Yes, this was predicted. The millennials are, on average, marrying later and having kids later but they're still marrying, having kids, and buying houses.  

Monday, August 17, 2020

Gaiters - Are they bad or did the news jump the gun (again).

Yes, I suppose that this is another COVID-19 post but I haven't written about COVID since April and March. Also - one could argue that this post isn't really about COVID. It's really about press coverage of emerging research (maybe any research) and COVID just happens to be the context.

You've probably seen the headlines or heard the news that the neck gaiters people have been wearing as face masks might not be working. Six days ago the headline was pretty scary: "Wearing a neck gaiter may be worse than no mask at all, researchers find".

OK, they did say "may" which could imply some uncertainty, but the coverage that I saw was pretty negative on gaiters. In fact, my employer has banned them based on these reports.

Four days ago, the headline was a little less scary: "Some neck gaiters may be worse than not wearing a mask at all, study shows". Now it says both "may" and "some".

Three days ago, the headline shifted again: "The results of this viral mask study found gaiters weren't effective - but it that true?" That's a very different headline and the article includes a quote from one of the researchers (Brian Labus):

“People have really gone overboard with their interpretation of this study. The goal of the study was not actually to evaluate masks” 

What??? They weren't even trying to evaluate masks? You wouldn't know it from the headlines but they were trying to develop a low-cost method that could be used to evaluate masks. 

In fairness, I should point out that all three articles include a link to the actual research report. Unfortunately, when major news outlets report on research, very few readers click through to the actual research (did you click my link?). Instead, people count on the news story to accurately summarize the research. In this case, the news blew it and focused on a peripheral issue.

In my experience, it's not unusual for news reports about research to do a poor job of representing the research. Sometimes it's intentional but often it's just sloppy reporting.

That said, there was a peripheral finding with a small sample size for a particular gaiter. That's far from conclusive but it should be enough to raise concerns and encourage further research on gaiters. I hope that research happens soon and gets better reporting.

Oh, about that sample size I mentioned in the previous paragraph? I could comment on it, but I won't. You should click through to the actual research study and see for yourself. 

Saturday, April 25, 2020

Wow. How did so many of us miss this?

I've tried to stick to my plan to write only one post about COVID-19 but it's been hard because there are so many data issues to talk about. As an aside - I think that StatNews is doing a pretty good job covering things.

But then I ran across this Wired story by Ferris Jabr. You should read it yourself but I'll be nice and quote the main point:

"Both newspapers and scientific journals frequently state three facts about the Spanish flu: it infected 500 million people (nearly one-third of the world population at the time); it killed between 50 and 100 million people; and it had a case fatality rate of 2.5 percent. This is not mathematically possible. Once a pandemic is over and all the numbers are tallied, its case fatality rate is simply the total number of deaths divided by the total number of recorded cases. Each country and city will have its own CFR, but it’s also common to calculate a global average. If the Spanish flu infected 500 million and killed 50 to 100 million, the global CFR was 10 to 20 percent. If the fatality rate was in fact 2.5 percent, and if 500 million were infected, then the death toll was 12.5 million. There were 1.8 billion people in 1918. To make 50 million deaths compatible with a 2.5 percent CFR would require at least two billion infections—more than the number of people that existed at the time."

Wow. How did we all miss this? Are we so innumerate that we didn't see 500 million and 50 million and immediately say "Hey, that's 10% not 2.5%"? Shame on us.

Beyond pointing out that none of us are paying careful attention, Jabr digs into the history behind these numbers and uncovers a lot of uncertainty about the Spanish Flu.

So here's where we stand.

  1. COVID-19. My original post is still correct. The data would matter greatly if we had it. But we don't. It's getting better but it's still inconsistent and unclear and we're still facing extensive uncertainly. 
  2. Spanish flu. This data would also matter greatly if we had it. But we don't have good data and, at this point in history, we never will.
The take-away? We need to get more comfortable with margins of error and ranges of estimates. Data literacy should emphasize the need to look beyond simple point estimates.

Along those lines, I've just started a simulation unit in one of my classes. Simulation is a great tool for dealing with high levels of uncertainty. If you want to see my opening lesson, it's right here:

Tuesday, April 14, 2020

Interesting Shifts in Consumer Spending

From one of my favorite blogs:

To me, the most fascinating aspect of this graph is that "groceries" initially jumped nearly 50% but now appears to be trending back to pre-stay-at-home levels while all other categories continue to decrease.

Much of the drop may be due to the sudden increase in unemployment but we can hope that some of it is due to people simply not having opportunities to spend. If people are saving money now, then maybe they'll splurge when this is over and help revive the economy.