Tuesday, July 31, 2012

New data point

Today I would like to announce the start of a new study, with n=1.  Results will trickle in sporadically from here on in.

His name is Finn.

This morning I spent a few minutes explaining to him about correlation and causation, and his uncle took confirmation bias.  I think he understood.

They say the best data can be explained in pictures, so I'll leave you with this:
Good data, good.  Please excuse some sporadic posting for a bit!

Monday, July 30, 2012

International data - beware the self reporting

Maybe it's just because the Olympics are on, but I've run in to a few interesting international statistics lately that gave me pause.

The first was regarding infant mortality.  After Aaron Sorkin's new show The Newsroom incorrectly reported that the US was 178th in infant mortality (really, you think there are 177 countries you'd rather give birth in?), I went looking for the infant mortality listings across the world.  The US does not typically do very well in terms of other industrialized countries.  

There are a few interesting reasons for that....we have a much larger population than most of the countries that beat us, and it's spread out over a much larger area.  Our care across areas/populations tends to be more uneven, states vary wildly on issues like access, health insurance, prenatal care, etc. Our records however, tend to be meticulous....there is very little doubt that we capture nearly all infant mortality that actually occurs.  This combination can put the US at a huge disadvantage in these statistics (10-30% according to the best published studies).

This raises the point of why Cuba tends to beat us.  Now, realistically speaking, if you or someone you love had to give birth, would you seriously pick Cuba over the US?  Would anybody?  And yet they look safer given the data....which is all self reported.  I have no problems believing that Singapore outranks us, but I'm skeptical of any country that might have an agenda.  Worldwide, there is actually very little consensus on what is a "live birth", and the US tends to use the "any sign of life" definition.  

On the other end of the spectrum, I saw this piece recently on gun control.  I've covered misleading gun stats before (suicides are often combined with homicides to get "death by gun violence" numbers).  One of the interesting facts the article above points out is that internationally, gun deaths are only counted when it's civilian on civilian violence.  This is certainly fine in the US...I would think we wouldn't want to count every time the police had to open fire, but in countries with, um, more questionable police tactics, this could cause some skewing (Syria was cited as one such example).  

Data is hard enough to pin down when you know the sources have no vested interest in misleading you....international rankings will never be free from such bias.

Saturday, July 28, 2012

Too hot to hire?

....or why psych undergrads would make lousy hiring managers.

I saw this study pop up on Instapundit, and while the number of "that happens to me all the time" jokes are infinite, I'm pretty sad this study got mentioned at all.  Here's the Router's recap:
Attractive women faced discrimination when they applied for jobs where appearance was not seen as important. These positions included job titles like manager of research and development, director of finance, mechanical engineer and construction supervisor.
Oh the sad sad existence of beautiful women.  To work so hard on your career and then get denied a job because you're too attractive.  Now, out of curiosity, exactly how many women got rejected from these jobs for this study?


This study didn't study women or men actually applying for jobs.  They studied what happens when you give a bunch of psych undergrads a huge stack of pictures, a list of job titles and say "sort these pictures in to groups of who you think would be most qualified for a job based solely on the pictures".  Seriously, that's what they did.  Read the full study here.

It turns out that when you ask 65 undergrads (mostly women) to rank a whole bunch (204) of photos of people using no criteria other than what they look like, people might judge other people based on what they look like.  There was some lovely statistical analysis in here, but at no point did they attempt to prove that asking a 20 year old (who presumably had no first hand knowledge about any of the fields other than psych) to sort a picture reflected at all what goes on in hiring offices.

In fact, this is what the "practical implications" section of the paper said:
Although the findings reported here demonstrate the “what is beautiful is good” and “beauty is beastly” effects, it is important to address the likelihood of such stereotypes influencing actual employment decisions. For example, in situations where there is a high cost of making a mistake, as would be the case for a hiring decision, one would expect the decision maker to rely more on individuating information, rather than on stereotypes about physical appearance. However, it is important to note that the bias for the physically attractive, unlike other stereotypes, seems to impact impression formation in a broader range of circumstances. Recent meta-analyses suggest that the what is beautiful is good effect is pervasive, even when the perceiver has additional information about the target   (Hosoda et al., 2003; Langlois et al., 2000). Attractiveness may influence decision  making at a subconscious level, where exposure to an attractive individual elicits positive feelings in the decision maker, causing him or her to judge the target more favorably (Eagly et al., 1991). Moreover, in situations where a decision maker is under a high cognitive load or under time pressure, he or she may be more likely to rely on stereotypes (Fiske & Taylor, 1991; Pendry & Macrae, 1994).
So there is some proof that people favor attractive people no matter what, but no similar proof that they might discriminate against an attractive person if they had real world information.  Which leads me to get a little weirded out by quotes like this from the researcher (in interviews, not the article):
"In every other kind of job, attractive women were preferred," said Johnson, who chided those who let stereotypes affect hiring decisions. 
Putting aside the fact that equality in this case appears to mean that everyone should prefer attractive people....what hiring managers was she chiding?  The ones she never studied?  Since the largest bias against attractive women was found when the mostly female undergrads were asked about who was qualified for male dominated fields....does that say more about what men think about women in non traditional fields, or what women think about women in non traditional fields?

While I'm sure that physical appearance does make a difference in hiring practices, I would have loved to see a little more time dedicated mimicking the real world before announcing that women were facing discrimination in certain professions.  To allow these results to be propagated as proof of what goes on at legitimate companies is a bit of a stretch, and points the finger at people who never even got asked what they would do.  

Friday, July 27, 2012

Friday Fun Links

This is one of the coolest uses of graphic/animated data I've seen....it compares past Olympians to each other to show what the events would have looked like if the gold medalists from different years had competed against each other.  Swimming seems to have gained the most over the years, while the long jump seems more impervious to time.

This infographic looks innocuous, until you look at the upper right hand corner.  Cats have 72 hour days? (h/t junkcharts)

This is a useful page if you ever wanted to know what superhero your font of choice would be.  The only downside....no comic sans (asshole).

XKCD.com added a new page where he answers hypothetical questions with physics.  This weeks is "what would a mole of moles look like?"  Haven't we all wondered that at some point?

Thursday, July 26, 2012

Tracking the wild bad data

As someone who spent 3 years studying family dynamics in grad school, I was pretty interested in the NYT piece that ran last week on class divides in single vs married households.  The article generated a lot of buzz, and if you haven't read it, I would recommend it.

People seemed to either love or hate this article, and it's stirred up a whole lot of discussion online.  One of the more interesting points that got brought up though, was a discussion about why the focus was on single moms as opposed to deadbeat dads.

This led to some quoting of an interesting statistic regarding custodial parents and child support.  When I first read this statistic, it was from Amanda Marcotte over at Slate who put it this way:
.... in a substantial number of cases, the men just quit their families. That's why only 41 percent of custodial parents receive child support.
Now, I've perused internet comment boards enough to know that there are a LOT of men out there griping about how much they pay in child support.  I was a little shocked to read that apparently 59% don't give anything.  I clicked on the closest link she had provided.....which took me over to the NYT Economix blog and an item by Nancy Folbre. There was the stat again, except with a few more qualifiers:
In 2009, the latest year for which data are available, only about 41 percent of custodial parents (predominantly women) received the child support they were owed. Some biological dads were deadbeats. 
So that frames it a little differently.  It's still a little unclear from that statement, but it started to occur to me that this probably meant only 41% were up to date on their support payments...not that only 41% of non-custodial parents were paying.

I clicked on the link provided by Folbre, and got to the Census Bureau website, which put it all this way:
 In 2009, 41.2 percent of custodial parents received the full amount of child support owed them, down from 46.8 percent in 2007, according to a report released today by the U.S. Census Bureau. The proportion of these parents who were owed child support payments and who received any amount at all — either full or partial — declined from 76.3 percent to 70.8 percent over the period.
Now that's still a lot of deadbeats, but it is a slightly different picture from the one we originally started with.  When I clicked on the link from the Census Bureau snapshot to the report it originally came from, I noticed something else interesting....only about half of all custodial parents have court ordered support, and the non-payment stats above appear to reflect only what is happening in the court ordered cases.  The non court ordered cases are certainly hazy....30% of custodial parents said they never went to court because they knew the other person couldn't pay....but it is interesting that the quoted stats only apply to half of the custodial parent cases.

Overall, I must say I kind of enjoyed attempting tracking the evolution of a stat (in reverse).  It's not often you get to actually see how things evolve from the primary source to several steps out....and it was an interesting mental exercise.  Thanks for taking the journey with me.

Wednesday, July 25, 2012

Review and redraft - research in government

A few months ago, my father let me know that New Hampshire had passed a law that required the various government agencies to update their rules/statutes every few years (5 years? 7 years? Dad, help me out here).  I'm not entirely sure what the scope of this law was, but my Dad mentioned that it was actually quite helpful for his work at the DMV.  It had surprised him how many of their rules did not actually reflect the changing times, and how helpful it was to update them.  One of the biggest rules they had found to update was that in certain situations, they were still only allowed to accept doctor's notes from M.D.s....so anyone who used a nurse practitioner for primary care couldn't get an acceptable note....despite NPs being perfectly qualified to comment on the situations they were assessing.  It wasn't that the note needed to be from an MD, it was just that when the rule was written, very few people had anything other than a primary care MD.  I found the entire idea pretty good and proactive.

I was thinking about that after my post yesterday on South Dakota's law regarding abortion risk disclosure.  I was wondering how many, if any, states require that laws based primarily on current scientific research  review those laws in any given time period.

Does anyone know if any states require this?  Or is this solely up to those who oppose certain laws to challenge things later?  

Tuesday, July 24, 2012

Correlation and Causation - Abortion and Suicide meet the 8th circuit

Perhaps it's lawyer's daughter in me, but I think watching courts rule on presentation of data is totally fascinating to me.

Today, the 8th Circuit Court of Appeals had to make just such a call.

The case was Planned Parenthood v Mike Rounds and was a challenge to a 2005 law that required doctors to inform patients seeking abortions that there was "an increased risk of suicide ideation and suicide".  This was part of the informed consent process under the "all known medical risks" section.

Planned Parenthood challenged on the grounds that this was being presented as a causal link, and was therefore was a violation of the doctor's freedom of speech.

It's a hot topic, but I tried to get around the controversy to the nuts and bolts of the decision. I was interested how the courts evaluated what research should be included and how.

Apparently the standard is as follows:

...while the State cannot compel an individual simply to speak the State’s ideological message, it can use its regulatory authority to require  a  physician to provide  truthful,  non-misleading  information relevant to a patient’s decision to have an abortion, even if that information might also encourage the patient to choose childbirth over abortion.”  Rounds, 530 F.3d at 734-35; accord Tex. Med. Providers Performing Abortion Servs. v. Lakey, 667 F.3d 570, 576-77 (5th Cir. 2012).  
So in order to be illegal, disclosures must be proven to be "“either  untruthful, misleading or not relevant to the patient’s decision to have an abortion."

It was the misleading part that the challenge focused on.  The APA has apparently endorsed the idea that any link between abortion and suicide is NOT causal.  The theory is that those with pre-existing mental health conditions are both more likely to have unplanned pregnancies and to later commit suicide. It was interesting to read the huge debate over whether the phrase "increased risk" implied causation (the court ruled causation was not implicit in this statement).

Ultimately, it was decided that this statement would be allowed as part of informed consent.  The conclusion was an interesting study in what the courts will and will not vouch for:

We acknowledge that these studies, like the studies relied upon by the State and Intervenors, have strengths as well as weaknesses. Like all studies on the topic, they must make use of imperfect data that typically was collected for entirely different purposes, and they must attempt to glean some insight through the application of sophisticated statistical techniques and informed assumptions. While the studies all agree that the relative risk of suicide is higher among women who abort compared to women who give birth or do not become pregnant, they diverge as to the extent to which other underlying factors account for that link.  We express no opinion as to whether some of the studies are more reliable than others; instead, we hold only that the state legislature, rather than a federal court, is in the best position to weigh the divergent results and come to a conclusion about the best way to protect its populace.  So long as the means chosen by the state does not impose an unconstitutional burden on women seeking abortions or their physicians, we have no basis to interfere.
I did find it mildly worrisome that the presumption is that the state legislators are the ones evaluating the research.  On the other hand, it makes sense to put the onus there rather than the courts. It's good to know what the legal standards are though....it's not always about the science.

Monday, July 23, 2012

Political ages...mean vs median?

I just found out The Economist has a daily chart feature!

Today's graph about age of population vs age of cabinet ministers is pretty fascinating:
It did leave me with a few questions though.....who did they count as cabinet ministers?  I don't know enough about the governments in these countries to know what that equates to.  Also, why average vs median?  

I initially thought this chart might have been representing Congress, not the Cabinet.  I took a look at my old friend the Congressional Research Service Report and discovered that at the beginning of the 112th Congress in 2011, the average age was  57.7 years, which would make this chart about right.  I had to dig a bit further to get the ages of the Cabinet, but it turns out their average age is 59.75.  I was surprised the data points would be so close together actually....especially since that 57.7 was for Jan 2011, so it's actually 59.2 or so now.  

In case you're curious, 7 members of the cabinet are under 60.  The youngest is Shaun Donovan (46), Department of Housing and Urban Development.  The oldest is Leon Panetta (74), Department of Defense. Panetta is actually the only member over 70.  Half of them are in their 60s, 5 in the 50s, and 2 in their 40s.  

I felt a little ashamed I only could have given name/position to 5 of them before looking them all up.  That's not great, especially when you realize I'm counting Biden.  Still, I comforted myself with the fact that I bet that beats a very large percentage of Americans.  

A quick look for other data suggests that median age of populations is the more commonly reported value.  The median age of the cabinet was actually 61, in case you're curious.

Sunday, July 22, 2012

Weekend Moment of Zen 7-22-12

This is a useful flowchart/infographic from Lapham's Quarterly for those who routinely get accused of witchcraft:

Hopefully your weekend went well enough that you didn't need this.  Otherwise I'd feel bad I didn't post it earlier.

Saturday, July 21, 2012

Are law schools liable for misleading statistics?

An interesting snippet from over at the Volokh Conspiracy, where former students sued their law school for publishing misleading statistics.

The court ruled that the salary statistics published by the school were truly misleading, but in the end caveat emptor prevailed.  Apparently the schools had published average salary data, but only for those students who actually got jobs.  The court ruled that:
....even though Plaintiffs did not know the truth of how many graduates were used to calculate the average salary, at the very least, it is clear that the Employment Report has competing representations of truth. With red flags waiving and cautionary bells ringing, an ordinary prudent person would not have relied on the statistics to decide to spend $100,000 or more.
I do love legal language at times, and I was fairly amused by the phrase "competing representations of truth". While in this case it was clear cut what information would have been most useful to the consumer, it's often unclear what statistical breakdown represents "actual reality" and such.  I did think that perhaps the court was giving the public too much credit though, when it cited what an "ordinary prudent" person would do (or is it just that not many prudent people exist?).

I've been reading Tom Naughton's blog quite a bit lately, and he often quotes his college physics professor's advice to all of his students.  It's a good quote, one that I think should be taught to all students freshmen year of high school.  In fact, it should have been used in this court decision:  "Learn math.  Math is how you know when they're lying to you."

Friday, July 20, 2012

For the philosophy majors

My younger brother's in town, which means I'm going to wind up having some excellent philosophical debates over the next few weeks.

I like these sorts of debates because they are pretty easy to deconstruct, as opposed to scientific or data analysis debates.  Saturday Morning Breakfast Cereal managed to condense the summary in to one panel:
Glad you're around little brother!  Missed you!

Thursday, July 19, 2012

Why do women quit science?

A week ago, I got forwarded this NPR article called "How Stereotypes Can Drive Women To Quit Science".  It was sent to me by a friend from undergrad, female, successful, with both an undergrad and a grad degree in engineering.  She found it frustrating, and so do I.

Essentially, the article is about a study that tracked female science professor's discussions at work (using some very cool/mildly creepy in ear recording devices), and came to the conclusion that women left science fields not because they were being overtly discriminated against, but because they're scared that they might be.  This panic is apparently called "stereotype threat", and is explained thusly:
When there's a stereotype in the air and people are worried they might confirm the stereotype by performing poorly, their fears can inadvertently make the stereotype become self-fulfilling.
I figure this is why I only routinely make typos when someone is watching me type (interestingly, I made two just trying to get through that sentence).

Anyway, the smoking gun (NPRs words, not mine) was that:

When male scientists talked to other scientists about their research, it energized them. But it was a different story for women. "For women, the pattern was just the opposite, specifically in their conversations with male colleagues," Schmader said. "So the more women in their conversations with male colleagues were talking about research, the more disengaged they reported being in their work."Disengagement predicts that someone is at risk of dropping out. There was another sign of trouble.When female scientists talked to other female scientists, they sounded perfectly competent. But when they talked to male colleagues, Mehl and Schmader found that they sounded less competent.
The interpretation of  this data was curious to me. I wasn't sure that social identity threat was the first theory I'd jump to, but I figured I'd read the study first.

It took me a little while to find the full paper free online, but I did it.  I got a little hung up on the conversation recording device part (seriously, it's a very cool way of doing things....they record for 50 seconds every 9 minutes for the work day to eliminate the bias of how people recall conversations....read more here).

Here are the basics:  The sample size was 19 female faculty from the same research university.  Each was then "matched" with a male faculty member for comparison.  I couldn't find the ages for the men, but they were matched on rank and department.  It appears the 19 women were out of 32 possibilities.  I'm unclear whether the remainder were unavailable or whether they declined. Genders did not have a difference in their levels of disengagement at the beginning of the study.

Unfortunately, they didn't elaborate much on one thing I had a lot of questions about: how do you define competence.  They only stated that two different research assistants ranked it.  Since all of the researchers in this study were social psychologists, presumably so were their assistants.  It concerned me a bit that science faculty was being rated by people that wouldn't know actual competence, merely the appearance of it (the study authors admit this is a weakness).

Another interesting point is that job disengagement was only measured up front.  When I had initially read the report on the study, I had inferred that they were taking data post conversation to see the change.  They weren't.  They took it up front, then found that the more disengaged women had a higher percentage of total discussions about work with men than the other women were.  It occurred to me that this could merely be a sign of "female auto pilot mode".  Perhaps when women are at ease they share more about their personal life?  The researchers admit this as a possibility, but say it's not likely given that they sound less competent....as assessed by people who didn't know what competence sounded like.

One point not addressed at all in this study was the seniority of the people the participants were talking to.  In traditionally male dominated fields, it is likely that at least some of the men they ran in to were the chairs of the department, etc, meaning that these women were probably talking to a more intimidating group of men than women.  Women who talk heavily about research and less about personal lives may have run in to more senior faculty more often.  As the study took place over 3 days, it could conceivably be skewed by who people ran in to.  Additionally, I was wondering about the presence of mentoring and/or women in science type groups.  Women in science frequently meet other women in science through these groups, and there could have been some up front data skewing there.

It's also important to note that for every measure of disengagement in the study, the results were between 1.5 and 2 (on a scale of 1 to 5).  While statistically significant, I do wonder about the practical significance of these numbers.  If asked whether you agree or disagree with the statement "I often feel I am going through the motions at work", how accurately could you answer, on a scale of 1 to 5?

Overall this study seemed very chicken and egg to me.  I'm not convinced that it's implausible that women simply share more of themselves at work, especially when they're comfortable, as opposed to the sharing itself making women more comfortable at work (there's nothing worse at work than an awkward overshare).   I'm still not sure I get where you'd extrapolate stereotype threat unless it was the explanation you'd already picked.....I did not see any data that would point to it independently.

I'd like to see a follow up study in ten years to see if these women did actually drop out at higher rates than their male colleagues, and what their stated reason for leaving was.  Without that piece, any conclusions seem incredibly hypothetical to me.  One of the things that drives me a bit bonkers when discussing STEM careers is very few people seem interested in what the women actually doing these careers think about why they choose what they do or do not do.  I've never seen a study that walked in to an English class and asked all the women why they weren't engineers.  Likewise, if more of these women quit than the men, I'd like to see why they said they did it.  Then perhaps we can get in to the weeds, but won't somebody tell me why women actually think they're quitting?

I looked through the references section and couldn't find a paper that addressed this question.

Anyway, I think it's important to remember that when reading a study like this, you have to agree with all the steps before you can agree with the conclusions.  Is measuring snippets of conversations and having them coded by research assistants a valid method of determining how women function in the workplace?  Is 19 people a big enough sample size?  Should level of disengagement at work be controlled for possible outside events that might be causing them to feel less engaged?  Should the women in question be asked if they felt stereotype threat, or is that irrelevant?

Most importantly, should NPR have clarified that when they said "stereotypes can drive women out of science" they meant "theoretical stereotypes that may or may not have been there and that women may or may not have been afraid of....and none of these women had actually quit we just think they might?".  You know, just hypothetically speaking.

What is STEM anyway?

I've been trying to work on a post about some further research on women in STEM fields, and I keep getting bogged down in definitions.  I am currently headed down the rabbit hole of what a "STEM job" actually is.

I found out some interesting things.  According to this report, my job doesn't count as a STEM job, despite the fact that I work with nothing but math and science (alright, and some psych).  It's not the psych part that excludes me however, it's actually that I work in healthcare.  Healthcare, apparently is excluded completely.

So if I were performing my same job, with the same qualifications, in a different field, I'd have a STEM job.  Since I report in to a hospital however, I don't have one.

Your doctor does not have a STEM job.  Neither does your pharmacist, dentist, nurse, or anyone who teaches anything on any level.  Apparently if you run stats for the Red Sox, you're in a STEM job, but do the same thing for sick people, and it doesn't count.


Wednesday, July 18, 2012

Once you get the color's down, it's rather lovely

I lost track of which color was which quite frequently, but if you can get over that, this is stunning:

Tuesday, July 17, 2012

Deadliest weapons and causes of death

There's an apocryphal story in the international public health sphere about the time someone tried to figure out total mortality in Africa in any given year.  Apparently they went through the newsletters/press releases of  charities dedicated to various diseases, and found that if you added all the "x number of people die every year" numbers up, everyone in Africa died every year.  Twice.

While there's likely some data inflation there, the other explanation is that it's really hard to classify causes of death (I've covered some of this before).  Even with infectious disease, this can be tricky.  If an HIV positive person contracts tuberculosis and dies, do they go under HIV mortality, or tuberculosis?  If malnutrition leaves on susceptible to other infections, what's the real cause of death?  How about a bad water supply that carries ringworm?

I bring this up because I saw a fascinating stat today over at the New Yorker (via Farnam St):

What Is The Most Effective Killing Machine Man Has Ever Seen?Mosquitoes.
There has never been a more effective killing machine. Researchers estimate that mosquitoes have been responsible for half the deaths in human history.Malaria accounts for much of the mortality, but mosquitoes also transmit scores of other potentially fatal infections, including yellow fever, dengue fever, chikungyunga, lymphatic filariasis, Rift Valley fever, West Nile fever, and several types of encephalitis. Despite our technical sophistication, mosquitoes pose a greater risk to a larger number of people today than ever before. Like most other pathogens, the ciruses and parasites borne by mosquitoes evole rapidly to resist pesticides and drugs.
via “The Mosquito Solution,” ($$$) The New Yorker, July 9 & 16, 2012, p. 40
Definitely made me a bit nervous, especially since it seems malaria, etc would actually be some of the more accurately counted causes of death.  So, um, take care of yourselves this summer, okay?

Monday, July 16, 2012

STEM and Title IX, stop me before my head explodes

I actually tried to write this post on Saturday.  I was too angry, and it turned out pretty unintelligible.  Here's take two, written after venting to my father (the lawyer who encouraged me to follow my interests in math and science).  I generally try to avoid politics on this blog, but this one hit too close to home.  If you don't want a rant, feel free to stop reading.  We'll be back as usual tomorrow.

I recently ran across the news that there are groups pushing to expand Title IXs reach in to the STEM fields. The theory is that Title IX should not just apply to sports, and that since such a great gender disparity exists in (some) STEM fields, they are a prime target for reform.

As a female with an engineering degree, I am appalled by this.  That is the polite way of saying it.  If you didn't get that, let me spell it out for you:  To all the lawyers, women's studies, sociology and other liberal arts majors out there who haven't taken a real science class since high school yet think you know anything about math or science education.....KEEP YOUR GODDAMN HANDS OFF MY DEGREE.

We mocked you in college.  We watched you party it up, day after day, bragging about how you turned in term papers on books you didn't read, and how little work you had to do to get by.  We grit our teeth and hunkered down, knowing that some day we'd at least launch in to better jobs that fit our passions and truly helped move the world along, and we'd make better money to boot.  We took pride in the fact that we were the few who chose a harder path, and that our degrees actually meant we learned something.  Now, the very people we looked down on are coming to "save" us.  Fantastic.

Is it not enough that we as a group already keep America from sliding even further down the math and science score list?  Now you want to accuse all the men I went to school with or got taught and mentored by of being sexist?  To suggest that they are not where they are because they were some of the best and brightest but because they systematically excluded women?  What are you saying about me?  That I'm some sort of victim who didn't know it?  That my anger at you is merely Stockholm syndrome?  Let me clue you in to something: the only people who ever made me feel bad about my love of math, science or computers were those who didn't love math, science or computers.  The only people who ever suggested that math might be too hard for me, were those for whom math was too hard for.  For as much lip service as we pay to the value of STEM fields, plenty of people think you're weird if calculating 5 times 7 isn't a challenge without a calculator.  None of these people are male engineers.

That's the emotional part of my argument.  Here's the rational part (you can tell it's rational, because I'm putting it in list form...that's some engineer logic right there).

  1. The people attempting to push women in to STEM fields often have no idea what STEM fields are actually like.  Penelope Trunk, a blogger who has started three different companies, wrote a great piece a while ago about how it drives her nuts when journalists and academics bemoan the lack of women in tech start up.  One of her major points was that these women have never lived that life, despite it being available to them, and how dare they then imply that other women should take a path they didn't?  
  2. No one has proven that the disparity in STEM majors is because of sexism on the college level.  Not much more to say except:
  3. The implication that women don't go in to STEM fields because of sexism is stupid.  And asinine.  And naive.  When I was looking in to engineering programs, I was treated very well.  So were all of my classmates.  Engineers are not an exclusive bunch.  Very few of us were popular in high school, and it shows.  You're actually interested in talking about what we're talking about?  Come on in!  I have rarely, if ever, heard anyone of either gender say "I wanted to be an engineer, but no program would accept me".  I actually will buy that there's sexism in math and science teaching, but not at the college level.  By the time you get to the college level, you already know if you like math and science or you don't.  If discrimination is happening, it's happening at the super female dominated elementary/middle school/high school level.  Title IX will do nothing but punish universities for issues that started much earlier.
  4. Title IX is too limited in scope to address the real problems. I think workplaces in America should be more family friendly.  Whether people are taking care of young kids, or aging parents, everyone needs a break sometimes.  I'm not  advocating any  legislation to address this, just saying that in general I'd love to see a bigger push for it for workers of all ages and both genders.  I'd also like to see better more engaging science and math education for middle school and high schoolers.  Also, I'd like someone to give me a pony.  Any of those plans could (hypothetically) could increase the number of women in STEM jobs.  Title IX can't touch either of those points, or the pony thing.  If we've learned one thing from Title IXs first run, it's that you can get more women playing sports, but you can't make female professional athletes as wealthy as men.  Sometimes the world just is what it is, and forcing colleges to do things differently can only go so far if they weren't the problem to begin with.  
  5. STEM fields are something you have to know you want to enter immediately, or you've missed the boat.  This is a bit of a weird one, but stay with me.  For my engineering degree, I was required to take 6 classes that were not engineering.  That's all I got to pick over 4 years.  From the moment you enter engineering to the moment you graduate, your whole degree is spelled out for you.  If you enter college thinking you like psych, but then deciding that physics was more your thing, you cannot transfer in to it without adding years on to your graduation date.  Transfer the other way however, and you will be just fine.  This means the spigot out of engineering always flows faster than spigot in.  It's why my class started at 200 and ended at 60.  Even enrolling 50/50 men and women would not stop more women from dropping out, and that's very hard to compensate for midstream. 
  6. STEM fields were always more impervious to bias, because there are definite right and wrong answers.  I remember a programming class I took in college had a rule: if the code doesn't compile, you get an F.  Once it compiled, you were guaranteed a "C", and from there every requirement you hit moved your grade up.  It didn't matter if you were male, female, or something from Mars, there was no leeway in your grade.  You knew every grade ahead of time, based on what your code could and couldn't do.  My professor could have been running men's rights groups out of his office, and with standards like that, he would have had a tough time putting any bias in the grade.  I've heard hundreds of stories from liberal arts majors about wonky grading from professors, but very few from engineers.  Engineers are more likely to come out saying that the class average was a 16%, so now anyone who got more than a 25% has an A.  It's wacky, but pretty egalitarian.
  7. Adding more women will not improve engineering, improving engineering education will improve engineering.  This NYT piece was widely forwarded and shared among my friends from undergrad.  Why?  Because it eloquently states that engineering degrees kind of suck to get.  They're hard, you get bad grades a lot, they can be boring, and the courses attempt to "weed you out" often gratuitously (lots of dues paying type activities).  The "math-science death march" is a real phenomena, and as someone who survived it I can categorically say the name is descriptive.  No one enjoys the first two years of an engineering degree....they survive them.  It pushes unqualified people out, but it pushes good people out too.  I refuse to believe that this is the only workable system.  Engineers don't think that way about anything else....why give up so easily in education?  Pour the money in to making the whole system better, then everyone will have more fun.
  8. Focusing on women can be bad for men.  After this news broke, it was quickly pointed out that this focus on women in STEM had to be really selective in it's concern.  Women absolutely flock to certain STEM professions....biology, vet medicine, pharmacy, allied health, nursing.  My mother and sister are nurses, and tend to get a bit put out that nursing seems to not be counted as STEM unless specifically pointed out.  In April, I went to a conference that showed some preliminary research that groups function best when the gender distribution is somewhere between 30/70 and 70/30.  Too many or too few of either gender can skew a field.  If we're going to claim the benefits of diversity, that has to work both ways.  Some of this emphasis is getting in to really creepy "women must dominate everything worth having" territory, and it scares me.  No one would care about engineering if it didn't have a good paycheck attached.
  9. Focusing on women can be bad for women.  As I read people's reactions to this news this weekend, I read a lot of awful misogynistic things being said in the comments sections.  I'm sure many will take this as proof that sexism really is at play here, and that this reform needs to happen.  I don't see it that way.  What I do see is that you're telling one group (men) that they didn't really earn what they got, and that another group (women) inherently deserves it more.  This gets people defensive, and makes them say really lousy things to prove why they really did deserve it more.  Now, rather than talking about how we could really improve all of this, it reframes the whole conversation as a gender debate.  This leads people to make huge generalizations about gender, which almost never ends well for anybody.  Women claim men are all power hungry pigs, hoarding the good jobs for themselves.  Men start claiming women are inherently less dedicated, less technically minded, less intelligent, etc etc.  Honestly, most people of both genders would make terrible engineers.  That's fine.  That's why the pay tends to be good.  Even in a perfect world, we would most likely see gender disparities in many professions.  That's also fine.   Let's not paint 3.5 billion people with one brush in an attempt to obscure the fact that sometimes people just make different choices for reasons that vary as much as 3.5 billion people can vary.
I could go on.  I haven't even begin to touch on whether or not STEM degrees are really the golden ticket people presume, whether fostering sexist thinking in undergrad will worsen the plight of female professionals by ensuring that the men they work with will have a chip on their shoulder, or several other points that could be made.  I'm stopping here though because I'm sick of thinking about this.  It's hard to see something I love reduced to a political bargaining chip.  While I do agree that more gender parity (at least to the 30/70 level) is a good goal, I'm confident that there are non legislative methods for getting that up that would cause few unintended consequences.  In a time when our universities are churning out thousands of useless degrees to people with quickly expanding debt, should our number one priority really be to muck around with one of the few areas that's doing reasonably okay?

Sunday, July 15, 2012

Political Arithmetic - Voter ID laws

Update: Link fixed

Last week I put up a post slamming an infographic on fair market rent between states.  I was interested in the AVIs response, which end with "These are advocacy numbers.  Not the same as actual reality."

Advocacy and other political skewings of data are one of those things that shouldn't bother me, but do.  

I read headlines, knowing that I'm going to be driven nuts but the presumptions and projections, and yet I read things anyway.  It's a bad habit.

All that being said, I truly enjoyed Nate Silver's examination of the real effect voter ID laws might have on voter turnout in various states. 

He attempts to cut through all the partisan hoopla and to do a one person point-counterpoint.  An example:
But some implied that Democratic-leaning voting groups, especially African-Americans and Hispanics, were more likely to be affected. Others found that educational attainment was the key variable in predicting whom these laws might disenfranchise, with race being of secondary importance. If that’s true, some white voters without college degrees could also be affected, and they tend to vote Republican.
He also makes a fascinating point about the cult of statistical significance:
Statistical significance, however, is a funny concept. It has mostly to do with the volume of data that you have, and the sampling error that this introduces. Effects that may be of little practical significance can be statistically significant if you have tons and tons of data. Conversely, findings that have some substantive, real-world impact may not be deemed statistically significant, if the data is sparse or noisy.
On the whole, he concludes it will swing in the Republican direction for this election, but reminds everyone:
One last thing to consider: although I do think these laws will have some detrimental effect on Democratic turnout, it is unlikely to be as large as some Democrats fear or as some news media reports imply — and they can also serve as a rallying point for the party bases. So although the direct effects of these laws are likely negative for Democrats, it wouldn’t take that much in terms of increased base voter engagement — and increased voter conscientiousness about their registration status — to mitigate them. 
The whole article is long but a great read about how to assess policy changes if you're trying to get to the truth, rather than just prove a political point.

Saturday, July 14, 2012

Weekend moment of Zen 7-14-12

No comic, but a mildly humorous anecdote:

My wonderful husband and I took a child birth education class today.  The teacher was excellent, and spent a lot of time emphasizing that there were lots of different opinions about lots of things, but the focus should always be having a healthy baby/healthy mom.

She repeated this several times (clearly trying to avoid having any natural childbirth vs epidural debates) and then mentioned that you could read plenty of research about all sorts of different aspects of childbirth, but that it was really important to assess sample size, who did the study, etc etc.

I started to laugh a bit, and she looked at me and said "no really, you would not believe how many bad studies there are out there!".

Needless to say, I enjoyed this teacher immensely.

My kind of class right there.

Friday, July 13, 2012

Moral obligations and Lazy Truth

I was going to include this in a Friday link post, but I really felt it deserved it's own spotlight.  

There's a new gmail gadget called "Lazy Truth" that promises to send you a fact check email every time you receive a (forwarded) email it deems to be of dubious content.

I haven't tried it, so I'm not sure what it's set up to flag, or how accurate the "fact check" email is, but I was immediately intrigued.  I've actually been working on a much longer post that covers just this topic, so it's something I've been giving a lot of thought.

I've been mulling over the rise of Facebook/email/Twitter lately, and wondering.....for those of us who value our integrity and our truthfulness, and do not believe ends justify means, what exactly are the moral implications of hitting forward or share on information that we could have easily proven to be false if we'd checked?

I was wondering if I was the only one worried about this, when I came across a blog post from Dr Michael Eades.  He's a pro-low carb physician, who spends much of his time critiquing nutritional research.  In a post about the book "The China Study", he describes finding what he consider a great critique of it on another person's blog.  Then this:
.... I had fallen victim to the confirmation bias.  My bias was that Dr. Campbell was wrong, so I was more than happy to uncritically accept evidence confirming his error without lifting a finger to double check said evidence myself.  I knew that if a blogger somewhere had come out with a long post describing an analysis of the China study demonstrating the validity of all of Dr. Campbell’s notions of the superiority of the plant-based diet, I would’ve been all over it looking for analytical errors.  But since Ms. Minger’s work accorded with my own beliefs, my confirmation bias ensured that I accepted it at face value. 
Once the fact that I had succumbed to my confirmation bias settled in around me, I became suffused with angst.  I had tweeted and retweeted Ms. Minger’s analysis a number of times, giving the impression that I had at least minimally checked it out and had approved it.  I had emailed it to a number of people, many of whom, I’m sure, had forwarded it on.  I’m sure I played a fairly large role in the rapid dissemination of the anti Campbell/China study info.
In the end, he went back and realized that the post was good, but his panic attack was intriguing to me.  How many of us have had this same panic?  How many of us should have?  How many lousy graphs rip through Facebook like wildfire because no one bothers to double check if they're even valid?  Is the liar the person who created the graph, or do those who share it share some blame?

I don't pretend I have an answer for this.  I feel most of the people interested enough to read this blog probably do not fall in the category of those who would easily share skewed information without thinking about it, but I am hoping for some thoughts/feedback from you all.

Are we so used to hearing politicians of all stripes seamlessly repeat bad data that we've come to view it as acceptable?  Is this just a fact of life?  Is it possible that we will be saved by widgets like the one above?   Does religion matter, or is this an overall moral issue? Does confrontation work with this sort of thing?  Or is this something I just have to learn to live with?

Thursday, July 12, 2012

Soviet Propaganda, Infographic Style

In "How to Lie With Statistics", the author frequently comments about Soviet Propaganda and how bad it is. Being a member of a cynical generation, Huff's annoyance at an oppressive regime using data skewing to seem better than it was seemed almost quaint....I mean of course they were.

Even given my cynicism and lack of Russian skills, I have to admit these infographics from the Duke U library are pretty interesting.

This one's my favorite, because none of the bar heights make any sense:
Moral of the story?  Every time you share a bad infographic, the Communists win.

Wednesday, July 11, 2012

Good hospital/Bad hospital

Several years ago, back when I was working in the Emergency Department, I had a rather fascinating encounter with a patient's wife.  It was late in the evening on a Friday....a generally bad time to come in to the ER....and she had brought her husband in with a large cut on his arm.  He needed stitches for sure, but the place was hopping that night, and so she, her husband, and her two small children had been stuck in the waiting room for several hours.  After some time, she had come in asking me when someone was going to come get him.  At that point, I think they still had 4 or 5 people ahead of them, and I let her know.  

She (fairly understandably) flipped out.  

As I tried to calm her down, she started to lecture me about how long they had been waiting....and then proceeded to let me know that this wait had come after she had driven her husband over an hour and a half to get there.  "You are SUPPOSED to be the best hospital in the country" she raged.  "How can you be if you make patients wait so long????".

Now I had the "why am I waiting so long" conversation with literally thousands of patients in my time in the ER, but something really struck me about this poor woman's frustration.  She had brought her husband to a hospital that was supposed to be the best (this particular hospital bounces around the top 5 in the country pretty routinely), but not for what he needed done that night.  What he needed was a simple set of stitches, the likes of which nearly any doctor in the country could have done.  When I took a look at her address, I realized she had driven by at least five different hospitals with ERs to get to ours.  Most likely any one of them would have gotten her faster service with the same quality of care.  In fact, within the next few years, three of them would devise marketing strategies around publicizing that fact.  The problem is, this woman had confused "the best" with "good at everything".  

When it comes to hospitals, that's just not true.

Given my professional experience, I was unsurprised  to see Time reporting that not one of the 17 best hospitals (according to US News and World Report) made the consumer reports list of safest hospitals.  

There's a couple reasons for this, some good and some bad:
  1. Best hospitals tend to be large teaching hospitals.  Large teaching hospitals have a lot of residents. Residents can be a little dicey.
  2. Best hospitals tend to see huge numbers of patients.  This can complicate things.
  3. Best hospitals tend to see cases other hospitals can't help.  Almost all of your top hospitals will have higher mortality rates than smaller community hospitals.  Why?  Because unless you're literally DOA, the first thing a small hospital will do with a really sick patient is to ship them off to a hospital with a good intensive care unit.  The top hospitals almost never transfer their patients.
  4. Best hospitals are ranked in large part on how they treat the toughest cases.  The more unique your condition, or the worse your risk factors, the more selective you need to be.  The more routine your complaint, the more a top hospital can actually work against you....you're going to be one of many, and nothing makes you stand out.
  5. Large medical centers, specifically in urban settings, give away a lot of free care to a lot of high risk populations.  These patients are unlikely to do well in any setting, and can skew the data tremendously.  Location counts.
There's constant strife over how to accurately rank hospitals, because professionals skew hospital rankings in the direction of valuing medical uniqueness.  Patients on the other hand, tend to value things like "comfort of chairs in the waiting room" nearly as high as they do "physician competence".  Patient's also claim to want things that they don't really....for example nearly everyone says they value physician competence over bedside manner, yet patient's routinely rate physicians with good bedside manner higher than those with good technical skill.  Patient's receiving appropriate care also file plenty of complaints if it wasn't the care they expected.  No hospital ranking is going to hit every part of the hospital equally regardless of who ranks it, and every department can have a bad day.   

I don't have a lot of answers to these issues, but it's important to keep them in mind when you hear ideas for improvement.  While the Time article got a bit too political for my taste, it is true that patients can only make informed decisions if the information they have is what they think it is.

Tuesday, July 10, 2012

19 women don't like sports

Normally this is the sort of thing Joseph's blog specializes in, but I couldn't let this one slide.

I've spent all of last week and this week listening to construction workers traipsing around my basement, working diligently to finish it so we can finally have the sports room my husband's impressive memorabilia collection deserves.  Thus, it distressed me a bit to see the headline that married women only watch sports for the sake of their husbands.  Is my interest in the sports room one big lie? Has my Red Sox fandom all been a fraud?  Should I toss out all my vintage basketball cards from the 80s?  And football.....okay, I actually didn't like it all that much until I got married.  I'll give you that one.  Two out of three ain't bad.

Anyway, I pretty amused when Jezebel and other's quickly pointed out that the sample size for this study was 19.     19 women, all from around the University of Tennessee.  In case you're curious, The Bleacher Report ranked Knoxville the 44th best sports town in the USA.  Maybe my perception is skewed because Boston's #2, but I'm not sure that's an overly representative sample from an overly representative town.

Get some good Southie girls together and ask them what they think, I bet you'll get a wicked different picture.

Monday, July 9, 2012

Fair Market Rent and Another Dubious Infographic

I've seen this infographic a few places now, and it has been causing me some furrowed brow time:
Supposedly, this is a graphic showing how many hours you would have to work per week at a minimum wage job in order to afford a two bedroom apartment in each of the given states.  This version appears to be a year or so out of date, but here's the original report.

I had all sorts of questions about this when I saw it, so of course I went digging.  

To clarify the parameters, affordable is defined to mean 30% of income, and this chart assumes only one income earner per apartment.  Availability of low income housing or other programs is not taken in to account, which is probably where I find this chart most misleading.  Massachusetts has a fairly extensive Section 8 housing program, and from my understanding New York and California do as well.  I couldn't find a ranking for the state distribution of aid levels, but I'd wager the less affordable the state, the more they give out in assistance.

As for the fair market value rents....I couldn't find where they got their figure from.  Rents in Massachusetts vary wildly between the 3 largest city areas.  Boston rents run high....mostly because students rent most of the apartments near the colleges.  Springfield and Worcester however are much cheaper.  The MA website for Section 8 housing cites the difference between Boston and Worcester as almost $450 a month.  It appears the number used above is an average of several areas.  

If you dig further in the report however, it becomes even more interesting.  Apparently New England is the only section of the country that doesn't report whole counties when reporting fair market rates for renters, New England only reports rates for metro areas and surrounding communities.  Is the northeast really that much pricier than the rest of the country, or does their reporting just make them look that way?

While I ultimately appreciate the issue at hand with this chart, I think it would be nice to see a more comprehensive chart including states efforts to address the high housing cost.  On the chart above, NH appears slightly more affordable, but if you google "section 8 housing nh" you will find a lot of people telling you to save yourself the trouble and move to Massachusetts.  Bigger cities tend to mean higher rents AND more social programs.  Throwing them all in to one big average is not the best way of representing information in a usable fashion.

Friday, July 6, 2012

Friday Fun Links 7-6-12

Between the heat and being 8 months pregnant, running to catch the bus is pretty much more than I can handle these days.  Still, it's nice to know my age doesn't preclude me from competing in the Olympics.  

Apparently I'm on the wrong end of the bell shaped curve if I want to win a medal though....

If sports aren't your thing, how about a summer romance?  What, you're trapped in the friend zone?  Here's the stats on whether you should try to get out or not.

No summer vacation?  Stuck at work?  Use data?  Here's Juice Analytics new chart chooser (2.0) to help figure out how best to present your data.  Haven't tried it yet, but it looks awesome.

I've written before about retractions and their impact on public trust...but this was pretty stunning.  Yoshitaka Fujii, a Japanese anesthesiologist, has been found to have faked data in 172 published studies, dating back to 1993.  That's a record.

My bff from college is from West Virginia, and always told me that coal is a big deal there.  Turns out she wasn't exaggerating....apparently it matters more than political party in how people vote.

James over at I don't know but.... had a good post about the inaccuracies in the reporting about the Higgs boson.  Went more in depth than I could have, for sure.

That's it for now, have a good weekend!

Thursday, July 5, 2012

More physics...Einstein and teaching

With all the Higgs Boson excitement, I have had  physics on the brain lately.  Thus when Instapundit linked to this article from NPR, regarding how Einstein would not have been qualified to teach high school physics, I was intrigued.

The article is a rant against (some) licensing standards.  Licensing standards are really just performance metrics, which does make them an interesting study in data and outcomes.  Teaching is a particularly tricky profession to measure outcomes in, as every attempt to standardize (SATs, MCAS, etc) is typically met with objections about what real learning is.

I was fascinated by the Einstein question though.  While I certainly like Einstein, I was wondering if I'd really have wanted him as a physics teacher.  When I took psych stats in grad school, I averaged 107% in the class (there was lots of extra credit), but I was probably the worst resource there.  I can't explain basic stats worth anything to people, because it comes naturally.  That's why I like critiquing news stories....it's much easier to explain what's wrong with something when you have an example in front of you.  Explaining a t-test from scratch though?  I'll leave that to the professionals.

Aside from that, the study the NPR post points to is pretty interesting.  It compares licensed, unlicensed and alternatively credentialed teachers from NYC.  Interestingly, the most significant factor in teacher effectiveness tended to be years of experience (in the first few years) instead of credentialing.  All the differences however, were evaluated based on standardized testing scores, which may or may not be something you agree with as a metric.  Still, a fairly interesting and comprehensive look at the issue, if your interested in education metrics.

Update:  The purpose of education and outcome metrics are going to become increasingly important if this catches on (and I hope it does).

Higgs Boson...comic edition

It has nothing to do with statistics, but the Higgs Boson story has been the most exciting news I've heard in a while.  Physics was always my favorite of the sciences, and it's nice to see hard science reporting make major headlines.

Thanks to my science/math geek cred, I've gotten asked by a few people to break down what the big deal is, so I've been looking for a good, simple, comprehensive resource to point people to.  PhD comics apparently was all over this back in April, and I'm posting it here because I like it.  Yay for science!

Wednesday, July 4, 2012

4th of July, Census Bureau style

Here's hoping everyone had a relaxing 4th of July!

Today I learned that the White House sponsors two official Independence Day parties at the White House. One of them is for service men and women and their families, the other is for a broader group of friends of the White House.  I bring this up because apparently my younger brother finagled a ticket to the second one. Kind of makes my day feel a little lame, but hey, at least the house is coming along, and I'm the most relaxed I have been in a while.

I was looking for some good stats about the White House, but then I found this which I thought was equally interesting.  It's no West Lawn Party....but we here at Bad Data Bad do what we can with what we have.

Without further ado, here's some (year old) fun facts, courtesy of our Census Bureau:

The Fourth of July 2011

On this day in 1776, the Declaration of Independence was approved by the Continental Congress, setting the 13 colonies on the road to freedom as a sovereign nation. As always, this most American of holidays will be marked by parades, fireworks and backyard barbecues across the country.

2.5 million

In July 1776, the estimated number of people living in the newly independent nation.
Source: Historical Statistics of the United States: Colonial Times to 1970

311.7 million

The nation's estimated population on this July Fourth.
Source: Population clock <http://www.census.gov/main/www/popclock.html>


$3.2 million

In 2010, the dollar value of U.S. imports of American flags. The vast majority of this amount ($2.8 million) was for U.S. flags made in China.
Source: Foreign Trade Statistics <http://www.census.gov/foreign-trade/www/>


Dollar value of U.S. flags exported in 2010. Mexico was the leading customer, purchasing $256,407 worth.
Source: Foreign Trade Statistics <http://www.census.gov/foreign-trade/www/>

$302.7 million

Annual dollar value of shipments of fabricated flags, banners and similar emblems by the nation's manufacturers, according to the latest published economic census data.
Source: 2007 Economic Census, Series EC0731SP1, Products and Services Code 3149998231


$190.7 million

The value of fireworks imported from China in 2010, representing the bulk of all U.S. fireworks imported ($197.3 million). U.S. exports of fireworks, by comparison, came to just $37.0 million in 2010, with Japan purchasing more than any other country ($6.3 million).
Source: Foreign Trade Statistics <http://www.census.gov/foreign-trade/www>

$231.8 million

The value of U.S. manufacturers' shipments of fireworks and pyrotechnics (including flares, igniters, etc.) in 2007.
Source: 2007 Economic Census, Series EC0731SP1, Products and Services Code 325998J108

Patriotic-Sounding Place Names

Thirty-one places have “liberty” in their names. The most populous one as of April 1, 2010, is Liberty, Mo. (29,149) Iowa, with four, has more of these places than any other state: Libertyville, New Liberty, North Liberty and West Liberty.
Thirty-five places have “eagle” in their names. The most populous one is Eagle Pass, Texas (26,248).
Eleven places have “independence” in their names. The most populous one is Independence, Mo. (116,830).
Nine places have “freedom” in their names. The most populous one is New Freedom, Pa. (4,464).
One place with “patriot” in the name. Patriot, Ind. (209).
Five places have “America” in their names. The most populous is American Fork, Utah (26,263).
Source: American FactFinder <www.census.gov>

Early Presidential Last Names


Ranking of the frequency of the surname of our first president, George Washington, among all last names tabulated in the 2000 Census. Other early presidential names that appear on the list, along with their ranking, were Adams (39), Jefferson (594), Madison (1,209) and Monroe (567).
Source: Census 2000 Genealogy <http://www.census.gov/genealogy/www/freqnames2k.html>

The British are Coming!

$98.3 billion

Dollar value of trade last year between the United States and the United Kingdom, making the British, our adversary in 1776, our sixth-leading trading partner today.
Source: Foreign Trade Statistics <http://www.census.gov/foreign-trade/statistics/highlights/top/top1012yr.html#total>

Fourth of July Cookouts

More than 1 in 4

The chance that the hot dogs and pork sausages consumed on the Fourth of July originated in Iowa. The Hawkeye State was home to 19.0 million hogs and pigs on March 1, 2011. This estimate represents more than one-fourth of the nation's estimated total. North Carolina (8.6 million) and Minnesota (7.6 million) were also homes to large numbers of pigs.
Source: USDA National Agricultural Statistics Service

6.8 billion pounds

Total production of cattle and calves in Texas in 2010. Chances are good that the beef hot dogs, steaks and burgers on your backyard grill came from the Lone Star State, which accounted for about one-sixth of the nation's total production. And if the beef did not come from Texas, it very well may have come from Nebraska (4.6 billion pounds) or Kansas (4.1 billion pounds).
Source: USDA National Agricultural Statistics Service


Number of states in which the value of broiler chicken production was $1 billion or greater between December 2009 and November 2010. There is a good chance that one of these states — Georgia, Arkansas, North Carolina, Alabama, Mississippi or Texas — is the source of your barbecued chicken.
Source: USDA National Agricultural Statistics Service

Over 1 in 3

The odds that your side dish of baked beans originated from North Dakota, which produced 36 percent of the nation's dry, edible beans in 2010. Another popular Fourth of July side dish is corn on the cob. Florida, California, Georgia, Washington and New York together accounted for 68 percent of the fresh market sweet corn produced nationally in 2010.
Source: USDA National Agricultural Statistics Service
<http://usda.mannlib.cornell.edu/usda/current/CropProdSu/CropProdSu-01-12-2011_new_format.pdf> and

Please Pass the Potato

Potato salad and potato chips are popular food items at Fourth of July barbecues. Approximately half of the nation's spuds were produced in Idaho or Washington state in 2010.
Source: USDA National Agricultural Statistics Service

More than three-fourths

Amount of the nation's head lettuce production in 2010 that came from California. This lettuce may end up in your salad or on your burger.
Source: USDA National Agricultural Statistics Service

7 in 10

The chances that the fresh tomatoes in your salad came from Florida or California, which combined accounted for 71 percent of U.S. fresh market tomato production last year.
Source: USDA National Agricultural Statistics Service


The state that led the nation in watermelon production last year (750 million pounds). Other leading producers of this popular fruit included California, Georgia and Texas, each had an estimate of more than 600 million pounds.
Source: USDA National Agricultural Statistics Service

81 million

Number of Americans who said they have taken part in a barbecue during the previous year. It's probably safe to assume a lot of these events took place on Independence Day.
Source: Mediamark Research & Intelligence, as cited in the Statistical Abstract of the United States: 2011
<http://www.census.gov/compendia/statab/>, Table 1239