Author: bs king

The (Magnitude) Problem With No Name

/ bs king / 15 Comments

As most of you know, I am a big fan of amusing myself by coining new names for various biases/numerical tomfoolery I see floating around on the internet. I have one that’s been bugging me for a little while now, but I can’t seem to find a good name for it. I tried it out on a bunch of people around Christmas (I am SUPER fun at parties guys), but while everyone got the phenomena, no one could think of a pithy name. Thus, I turn to the internet.

The problem I’m thinking of is a specific case of what I’ve previously called Number Blindness  or “The phenomena of becoming so consumed by an issue that your cease to see numbers as independent entities and view them only as props whose rightness or wrongness is determined solely by how well they fit your argument”. In this case though, it’s not just that people don’t care if their number is right or wrong, it’s that they seem oddly unmoved by the fact that the number they’re using isn’t even the right order of magnitude. It’s as though they think that any “big” number is essentially equal to any other big number, and therefore accuracy doesn’t matter any more.

For example, a few weeks ago Jenna Fischer (aka Pam from the Office) got herself in trouble by Tweeting out (inaccurately) that under the new tax bill teachers could no longer deduct their classroom expenses. She deleted it, but while I was scrolling through the replies I came across an exchange that went something like this:

Person 1: Well teachers wouldn’t have to buy their own supplies if schools stopped paying their football coaches $5 million a year

Person 2: What high school pays their coach $5 million a year?

Person 3: 28 coaches in Texas make over $120,000 a year.

Person 2: $120,000 is not $5 million.

Person 3: Well that’s part of an overall state budget of $20-25 million just for football coaches. (bs king’s note: I couldn’t find a source for this number, none was given in the Tweet)

Person 2: ….

Poor person 2.

Now clearly there was some number blindness here….person 1 and 3 only seemed to care about the idea that numbers could support their cause, not the accuracy of said numbers. But it was the stunning failure to recognize order of magnitude that took my breath away. How could you seriously reply to a comment about $5 million dollar salaries with an article about $120,000 dollar salaries and feel you’d proved a point? Or respond to a second query with an overall state budget, which is an order of magnitude higher than that? It’s like some sort of big number line got crossed, and now it’s all fair game.

I suspect this happens more often the bigger the numbers get….people probably drive astronomers nuts by equating things like a billion light years and a trillion light years away. Given that I’ve probably done this I won’t get too cocky here, but I would like a name for the phenomenon. Any thoughts are appreciated.

Recreational Quantification

/ bs king / 2 Comments

On my recent post about hot drinks and esophageal cancer, Gringo made a comment about how quickly his Yerba Mate cooled down in the summer (30 minutes) vs winter (10-15 minutes). I was struck by this, because I find random numerical trivia about people’s daily life quite fascinating. I think this is mostly because many people don’t actually keep track of stuff like this, or if they notice it they don’t remember it.

While this phenomena is obviously probably related to numerical aptitude, I also think it’s probably related to something John Allen Paulos talks about. In an article about Stories vs Statistics, he posits that about 61% of people (update: he may have been joking with this number, there’s no source for it) see numbers as “rhetorical decoration” to stories, whereas the other 39% see numbers as “clarifying information”.

This reminded me of an exchange I had with my father last week when we were discussing how cold it was:

Dad: How are you surviving the cold down there?
Me: It’s been pretty chilly. I could tell it was cold because my walk from the train normally takes me 30 minutes, and this week I noticed it was taking 26 minutes without me consciously increasing my speed.
Dad: wow, that’s cold.
<5 more minutes of back and forth on walking speeds during various weather patterns, and how traffic lights/street crossings make the 4 minute time saving even more impressive>

I have come to understand that most people do not reach for anecdotes like this when they are trying to explain how cold it is, but it’s one of the best ways of communicating information like that to my Dad.

Interestingly, Paulos attributes this communication preference to our feelings towards Type 1 vs Type 2 errors. He posits that those who want to hear numbers are doing so because they are focused on avoiding Type 1 errors (seeing something that’s not there), and those who prefer stories are more interested in avoiding Type 2 errors (failing to see something that is there). I have no idea if he’s right about this, but personality typing based on statistical approaches is a thing I am totally on board with.

Anyway, I find myself counting and/or finding ways of quantifying all sorts of things as I go through life. Some of these are straightforward (I tracked my gas mileage for quite some time, I track my steps and resting heart rate, I have a particular obsession with hours of daylight), but some are a little more complex.

For example, every time I go to a concert, I always take note of the relative frequency of mixed gender groups vs male only groups vs female only groups. I started this because I attend a lot of concerts with my husband, and we got in a running discussion about “guy bands” vs “girl bands”. As I tried to quantify which was which, I realized that a strict gender breakdown sometimes hid information about the band’s core audience. AC/DC for example: the crowd there is 30-40% women, but almost all of the women are there with men. The number of male only groups was 3 to 4 times the number of female only groups. Interestingly, in many of the mixed gender groups there were more women than men, which is why the proportion was so high despite women not attending alone. Thus I put AC/DC in the category of a “guy band” that appeals to women, as opposed to a gender neutral band. In other words, it appears women are happy to attend, but only if someone else suggests it.

Since I started tracking this, I have seen two bands who appear to have truly equal gender appeal: Tom Petty and the Heart Breakers and Aerosmith.

The most male dominated concert I have ever been to was Judas Priest. The most female dominated concert was Ani Difranco. At neither of these concerts could I find a member of the minority gender unaccompanied by a member of the majority gender.

Another interesting breakdown is “couples concerts” or “date concerts” where you see very few people attending in mono-gender groups. TV on the Radio and a few other hipster bands I’ve seen appear to be like that. On the other side, when I went to see a Drag Queen Christmas, it was entirely the opposite. The audience was half male and half female, but since most of the men were (presumably) gay the groups that attended were mostly mono-gender.

All that being said, I’d be interested in hearing about random things that readers count/track/note when out and about, or your band examples. I understand I have rather idiosyncratic tastes in music, so I’d be interested in other examples.

5 Things to Know About Hot Drinks and Esophageal Cancer

/ bs king / 5 Comments

Fun fact: according to CNN, on New Year’s Day 90% of the US never got above freezing.

Second fun fact: on my way in to work this morning I passed an enormous fire burning a couple hundred yards from where the train runs. I Googled it to see what was happened and discovered it was a gas main that caught on fire, and they realized that shutting the gas off (normal procedure I assume) would have made thousands of people in the area lose heat. With temps hitting -6F, they couldn’t justify the damage so they let the fire burn for two days while they figured out another way of putting it out.

In other words, it’s cooooooooooold out there.

With a record cold snap on our hands and the worst yet to come this weekend, I’ve been spending a lot of time warming up. This means a lot of hot tea and hot coffee have been consumed, which reminded me of a factoid I’d heard a few months ago but never looked in to. Someone had told me that drinking hot beverages was a risk factor for esophageal cancer, but when pressed they couldn’t tell me what was meant by “hot” or how big the risk was. I figured this was as good a time as any to look it up, though I was pretty sure nothing I read was going to change my behavior. Here’s what I found:

  1. Hot means HOT When I first heard the hot beverage/cancer link, my first thought was about my morning coffee. However, I probably don’t have to worry much. The official World Health Organization recommendation is to avoid drinking beverages that are over 149 degrees F. In case you’re curious, Starbucks typically servers coffee at 145-165 degrees, and most of us would wait for it to cool for a minute before we drank it.
  2. Temperature has a better correlation with cancer than beverage type So why was anyone looking at beverage temperature as a possibly carcinogen to begin with? Seems a little odd, right? Well it turns out most of these studies were done in part to rule out that it was the beverage itself that was causing cancer. For example, quite a few of the initial studies noted that people who drank traditional Yerba Mate had higher esophageal cancer rates than those who didn’t. The obvious hypothesis was that it was the Yerba Mate  itself that was causing cancer, but then they noted that repeated thermal injury due to scalding tea was also a possibility. By separating correlation and causation, it was determined that those who drink Yerba Mate (or coffee or other tea) at lower temperatures did not appear to have higher rates of esophageal cancer. Nice work guys.
  3. The risk has been noted in both directions So how big a risk are we looking at? A pretty sizable one actually. This article reports that hot tea drinkers are 8 times as likely to get esophageal cancer as those who drink tea at lower temperatures, and those who have esophageal cancer are twice as likely to say they drank their tea hot before they got cancer. When assessing risk, knowing both those numbers is important to establish a strong link.
  4. The incidence rate seems to be higher in countries that like their beverages hot It’s interesting to note that the US does not even come close to having the highest esophageal cancer rates in the world. Whereas our rate is about 4.2 per 100,000 people, countries like  Malawi have rates of 24.2 per 100,000 people. Many of the countries that have high rates have traditions of drinking scalding hot beverages, and it’s thought that combining that with other risk factors (smoking, alcohol consumption, poverty and poorly developed health care systems) could have a compounding effect. It’s not clear if scalding your throat is a risk in and of itself or if it just makes you more susceptible to other risks, but either way it doesn’t seem to help.
  5. There is an optimum drinking temperature According to this paper, to minimize your risk while maximizing your enjoyment, you should serve your hot beverages at exactly 136 degrees F. Of course a lot of that has to do with how quickly you’ll drink it and what the ambient temperature is. I was pretty impressed with my Contigo thermos for keeping my coffee pretty hot during my 1.5 mile walk from the train station in -3 degrees F this morning, but lesser travel mugs might have had a problem with that. Interestingly I couldn’t find a good calculator to track how fast your beverage will cool under various conditions, but if you find one send it my way!

Of course if you really want to cool a drink down quickly, just move to Fairbanks, Alaska and throw it in the air:

Stay warm everyone!

New Year’s Updates and Experiments

/ bs king / 2 Comments

Hey hey! Happy (almost) new year!

New experiment: My Year in Surveys

I don’t typically do new year’s resolutions, but I do like this time of year for sitting back and taking stock of where things are and what I might like to focus on going forward.  I have a few ideas, but they’re really pretty vague to the point of being useless: be healthier, manage stress better, spend more time with my loved ones. As often happens when I am faced with vague requests, the idea floated through my mind that I wish I had some more data about what was going on.

It occurred to me that there’s actually no good reason I can’t get the data I’m looking for. I design surveys for people as part of my side work, why not design one for myself to gather data around what I’m up to on a daily basis? Thus my 2018 self-survey was born. It’s a work in progress, but here’s the general set-up:

  1. Every day I take the same  survey (built in Google Forms) that asks questions about my health, stress status, and family life.
  2. Every time I encounter a need for a new answer (or new question), I add it and track it going forward.
  3. Snarky/ridiculous answers are allowed and are built in to the survey. In fact my stress management section is kind of based on this and asks about both “Psychodrama of the Moment” and “What are you obsessing about today?”

So far it takes me <5 minutes to complete, and asks some questions I’m pretty interested to trend out. For example, on the stress management page I have a list of different feelings I might be having that day. I will be fascinated to see what feelings are my most commonly reported. I’ll be interested to see how the survey changes over the year, and I’ll probably be doing some sort of reports about what I’m finding. It’s possible I’ll end up abandoning the whole thing by mid-January, but I think the active updating part will  appeal to my tinkering/don’t like to get bored side.

Top posts update:

I did my “top posts of 2017” post 2 weeks ago thinking nothing could really change between then and the end of the year. Then my Dunning-Kruger post got linked to in an apparently popular Reddit thread and it claimed the top spot for the year. Teach me to jump the gun.

Read the headline update: 

I’ve talked before about how you should always read more than the headline on an article, and I’ve also pointed out how every time an article is posted on social media people seem to feel freer to move away from the original source material. This article captured a new phenomena that’s related to both: news outlets posting their own stories to Twitter under different (and misleading) text that doesn’t jive with their own headlines/articles. The Hill is apparently quite terrible about this, though I’m sure with Twitter moving to 280 characters they’ll clear this right up, right guys?

That’s all I got, see you all in 2018!

5 Interesting Resources for Snowflake Math Lessons

/ bs king

Happy National Make a Paper Snowflake Day (or National Make Cut Out Snowflakes Day for the purists)!

I don’t remember why I stumbled on this holiday this year, but I thought it would be a really good time to remind everyone that snowflakes are a pretty cool (no pun intended) basis for a math lesson. My sister-in-law teaches high school math and informs me that this is an excellent thing to give kids to do right before winter break. I’m probably a little late for that, but just in case you’re looking for some resources, here are some good ones I’ve found:

  1. Khan Academy Math for Fun and Glory  If you ever thought the problem with snowflake cutting is that it wasn’t technical enough, then this short video is for you. Part of a bigger series that is pretty fun to work through, this video is a great intro to how to cut a mathematically/anatomically(?) correct snowflake.
  2. Computer snowflake models There’s some interesting science behind computer snowflake models, and this site takes you through some of the most advanced programs for doing so. It seems like a fun exercise, but apparently modeling crystal growth has some pretty interesting applications. Gallery of images here, and an overview of the mathematical models here.
  3. Uniqueness of snowflakes Back in the real world, there’s an interesting and raging debate over the whole “no two snowflakes are alike” thing. According to this article,  “Yes, with a caution”, “Likely but unprovable” or “it depends on what you mean by unique” are all acceptable answers.
  4. Online snowflake maker If you’re desperate to try out some of the math lessons you just learned but can’t find your scissors, this online snowflake generator has you covered.
  5. Other winter math If you’re still looking for more ideas, check out this list of winter related math activities. In addition to snowflake lessons around symmetry, patterns and Koch snowflakes, they have penguin and snowman math.

Happy shoveling!

 

Pictures of the Season

/ bs king / 2 Comments

Happy day before Christmas/3 days after the solstice!

This time of year I’m always on the lookout for interesting seasonal data sets/visualizations, and I’ve found  some good ones this year.

The first is this really cool visual of how long the shortest day of the year is across the US (original at the WaPo here):

It’s interesting that moving a little over an hour south of where I grew up appears to mean I gained an extra 15-20 minutes of daylight on the darkest day of the year. My sister on the other hand is currently in Juneau, Alaska and is ruing her short days.

There’s also this Vox article from last year that shows how many Christmas trees are grown by state. There’s an (unlinkable) interactive map that I found really interesting, as it shows how many trees each state cuts. 4 states produces over a million trees, and I have to admit I could not have named them. If you’re bored, try to name them before you check it out. I’ll leave the answer in the comments.

The last interesting data set is from a paper a commenter left on my Eating Season post. It’s called “The Seasonal Periodicity of Healthy Contemplations About Exercise and Weight Loss: Ecological Correlational Study” and it’s a study that looks at Google search trends for the topics of “exercise” and “weight loss”. Apparently searches for “weight loss” and some related terms peak twice a year (in the winter and summer months) and searches for “exercise” peak in the winter. My first thought with the exercise searches was that the winter drove people to search for ways of exercising indoors. The authors apparently had the same thought, since they also decided to see if a rise in Google searches for “exercise” correlated with the latitude the search was coming from. It did:

Coming from a city that’s had freezing rain/snow for the last several days, I can say I’m all in on indoor exercising. Alternatively, if someone wants to suggest we just all hibernate for the next few months, I’d be good with that too.

GPD Year In Review: Top Posts of 2017

/ bs king / 1 Comment

As the year winds down, it’s always a good time to take a look back at the year and see what’s happened and what the hopes are for 2018. My capstone class has finished up and been graded, and in a few days I’ll get the official piece of paper that says I’ve finished my studies. While I’m not planning on leaving my current job at the moment, I have some consulting work lined up and want to spend some time pulling together some of my writing from over the years. I’ll keep myself busy, don’t you worry.

While I’m working on that, I figured I’d continue my tradition of reviewing my most popular posts of the year. It’s always fun to see what was popular at the time I wrote it and what continued in Google popularity after it went up. While some of my most popular posts continue to be old ones (Correlation/Causation Confusion, Bimodal Distributions and Immigration, Poverty and Gumballs are Perennial Favorites), this list is only posts that were written in 2017:

  1. Calling BS Read-Along This series that followed along with the syllabus for the Calling Bullshit class and the University of Washington was far and away my most popular of the year, helped out quite a bit by the professors Tweeting out links to my posts. Definitely one of my more fun blogging experiences.
  2. The Real Dunning-Kruger Graph At first I was sort of surprised to see this one this high on the list, but I realized that it’s popularity has been boosted by a steady stream of Google traffic. It appears that quite a few people had the same question I did, and hopefully my post helped them out.
  3. Immigration, Poverty and Gumballs Part 2: The Amazing World of Gumball  After my original Immigration, Poverty and Gumballs post went mini-viral, I put together this post to address some of the responses. Not quite as popular, but still gets some traffic.
  4. 10 Gifs for Stats/Data People In my perfect world, this would be my most popular post. In this one, stats and data gifs are still pretty niche.
  5. Using Data to Fight Fraud: the Carlisle Method Doing a follow up to this post is definitely on my 2018 to do list.
  6. 5 Things You Should Know About Orchestras and Blind Auditions I am glad to know that there are people in this world who were as interested in the study behind the anecdote as I was.
  7. A Loss for so Many A post I wish I never had to write, but one I was happy got shared.
  8. 5 Things You Should Know About the Backfire Effect With political polarization all around us,
    this post may be one of the more important ones I did this year….how to actually convince people of facts when they don’t agree with you.
  9. How You Ask the Question: NFL Edition More examples of how asking questions differently can generate different responses. This one produced some debate on other blogs about whether or not this was really an example of “the same question” or whether it was an example of slight wording changes changing the question entirely, but regardless I think it’s a good example of how little word choices make a difference.
  10. Perfect Metric Fallacy This post probably was one of my most gratifying, as it got passed around an office that was going through this exact issue. Hearing people’s reactions made me laugh.

Here’s to 2018!

 

5 Things About Personality and Cold Weather

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As I mentioned on Sunday, I’ve been itching to do a deep dive in to this new paper about how people who grow up in cold regions tend to have different personalities than those who don’t. As someone who grew up in the New England area, it’s pretty striking to me how every warmer weather city in the US seems more outgoing than what I’m used to. Still, despite my initial belief I was curious how one goes about proving that people in cold-weather cities are less agreeable. While the overall strategy is pretty simple (give personality tests to different people in different climates, compare answers) I figured there’d likely be some interesting nuance I’d be interested in.

Now that I’ve finally read the paper, here’s what I found out:

  1. To make the findings more broadly applicable, study multiple countries One of the first things I noticed when I pulled up the paper is that there were a surprising number of Chinese names among the author list. I had assumed this was just a US based study, but it turns out it was actually a cross-cultural study using both the US and China for data sets. This makes the findings much stronger than they would be otherwise.
  2. There are 3 possible mechanisms for climate effecting personality I’ve talked about the rules for proving causality before, and the authors wasted no time in introducing a potential mechanism to explain a cold weather/agreeableness link. There are three main theories: people in cold weather were more likely to be herders which requires less cooperation than farming or fishing, people in cold weather are more susceptible to pathogens so they unconsciously avoid each other, and people may migrate to areas that fit their (group) personalities. Thus, it’s possible that the cold doesn’t make people disagreeable, but rather that disagreeable people move to cold climates. Insert joke about Bostonians here.
  3. The personality difference were actually present for every one of the Big 5 traits. Interestingly, every one of the Big 5 personality traits was higher in those who lived in nicer climates: extraversion, agreeableness, openness to new experience, conscientiousness and emotional stability. The difference in agreeableness was not statistically significant for the Chinese group. Here are the differences, along with what variables appear to have made a difference (note: “temperature clemency” means how far off the average temperature is from  72 degrees):
  4. Reverse causality was controlled for One of the interesting things about the findings is that the authors decided to control for the factors listed in #2 to determine what was causing what. They specifically asked people about where they grew up to control for selective (adult) migration, and in the Chinese part of the study actually asked about prior generations as well. They controlled for things like influenza incidence (as a proxy for pathogen presence) as well. Given that the finding persisted after these controls, it seems more likely that weather causes these other factors.
  5. Only cold climates were examined One of the more interesting parts of this to me is what wasn’t studied: uncomfortably warm temperatures. Both China and the US are more temperate to the south and colder to the north. The “temperature clemency” variable looked specifically at temperatures that deviated from 72 degrees, but only in the low temperature direction. It would be interesting to see what unreasonably hot temperatures did to personalities….is it a linear effect? Do some personality traits drop off again? I’d be curious.

Overall I thought this was an interesting study. I always appreciate it when multiple cultures are considered, and I thought the findings seemed pretty robust. Within the paper and in the notes at the end, the authors repeatedly mentioned that they tried most of the calculations a few different ways to make sure that their findings were robust and didn’t collapse with minor changes. That’s a great step in the right direction for all studies. Stay warm everyone!

What I Wish I Was Reading: December 2017

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With guests at the house, a sick kiddo and snow in the forecast, I have had no time to read this new paper on how regional temperature affects population agreeableness. I will be doing so soon however, because as someone who’s heard a lot about how unfriendly Boston is I’d like some validation for my go to “we’re rude because we’re cold” excuse.

Funny story: when my out of town guests picked up their (4 wheel drive) rental car, the lady behind the counter mocked them and said “expecting some snow or something”? When they got to my house and we confirmed that there is actually snow in the forecast, they wondered why she was so condescending about it. We explained that for Bostonians, a forecast of 4-6 inches over 20 hours isn’t really “snow”. They informed me that in Seattle, they’d be calling out the National Guard.

Also, my sister-in-law (married to my teacher/farmer brother) has informed me her new parenting slogan is “There’s no such thing as bad weather, only bad clothes” we she apparently got from this book of the same name. I like this theory. It goes nicely with my adulthood slogan of “There’s no such thing as strong coffee, only weak people.”

I hope to have a review of the paper up on Wednesday this week, stay tuned.

The Assistant Village Idiot linked  to this article (via Lelia) about those with no visual memory. I’ve been pondering this as I’m pretty sure my visual memory has some gaps.  I can’t read facial expressions baseline, and one of my recurring stress nightmares is being handed documents/books that I recognize but can’t decipher the text. I feel something’s related here, but I have to reread the article before I comment further.

Also, I know I always chide people to read behind the headline, but this headline’s so good I’m pretty sure I’ll love it when I finally get to read it: 5 Sport Science Studies that “Failed”. The author specifically took note of studies he saw that asked interesting questions and got negative results. He wanted to talk about this to fight the impression that the only interesting findings were positive findings.

Work Hours and Denominators

/ bs king

I was talking to a few folks about work recently, and an interesting issue came up that I’d never particularly thought about before. I’ve mentioned in the past the power of denominators to radically change what we’re looking at, how averages might be lying to you, and how often people misreport “hours worked”…..but I don’t know that I’d ever put all 3 together.

When answering the question “how many hours do you work per day”, most full time workers generally name a number between 8 and 10 hours a day. Taken literally though, it occurred to me that the answer is really somewhere between 6 and 7 hours on average, as most people aren’t working on the weekends. So basically when asked “average hours per day” we assume “average hours per working day” and answer accordingly.

This is a minor thing, but it actually is part of why the actual “hours worked” numbers and the reported “hours worked” numbers don’t always add up. When people try to figure out how much the average American is working, they take things like vacation/holiday weeks in to account. The rest of us don’t tend to do that, and instead report on how much we worked when we worked full weeks. A slight shift in denominator, but it can end up shifting the results by a decent amount.

Not the most groundbreaking insight ever, but I always get a little interested when I realize we’ve all been assuming a denominator that’s not explicitly clarified.