Tag Archives: measurement

Analyst looks at “racial breakdown of [presidential election] polls”

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An analyst for RealClearPolitics takes a look at possible issues with the racial breakdown in the samples of  presidential election polls. A few of the issues:

First, as Chait repeatedly concedes, we don’t know what the ultimate electorate will look like this November. That really should be the end of the argument — if we don’t know what the racial breakdown is going to be, it’s hard to criticize the pollsters for under-sampling minorities. After all, almost all pollsters weight their base sample of adults to CPS (current population survey) estimates to ensure the base sample reflects the actual population; after that, the data simply are what they are.

It’s true that the minority share of the electorate increased every year from 1996 through 2008. But there’s a reason that 1996 is always used as a start date: After declining every election from 1980 through 1988, the white share of the vote suddenly ticked up two points in 1992. In other words, these things aren’t one-way ratchets (and while there is no H. Ross Perot this year, the underlying white working-class angst that propelled his candidacy is very much present, as writers on the left repeatedly have observed)…

“The U.S. Census Bureau allows for multiple responses when it asks respondents what race they are, and Gallup attempts to replicate the Census in that respect. While most pollsters ask two separate questions about race and Hispanic ancestry, Gallup goes a step further, asking five separate questions about race. They ask respondents to answer whether or not they consider themselves White; Black or African American; Asian; Native American or Alaska Native; and Native Hawaiian or Pacific Islander.”

In other words, how you ask the question could impact how people self-identify with regard to race and ethnicity, which could in turn affect how your weighted data look. This is a polling issue that will likely become more significant as the nation grows more diverse, and more multi-racial.

Trying to figure out who exactly is going to vote is a tricky proposition and it is little surprise that different polling organizations have slightly different figures.

I hope people don’t see stories like this and conclude that polls can’t be trusted after all. Polling is not an exact science; all polls contain small margins of error. However, polling is so widely used because it is incredibly difficult to capture information about whole populations. Even one of the most comprehensive surveys we have, the US Census, was only able to get about 70-75% cooperation and that was with a large amount of money and workers. Websites like RealClearPolitics are helpful here because you can see averages of the major polls which can help smooth out some of their differences.

A final note: this is another reminder that measuring race and ethnicity is difficult. As noted above, the Census Bureau and some of these polling organizations use different measures and therefore get different results. Of course, because race and ethnicity are fluid, the measures have to change over time.

Measuring “peak car” in the United States

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With data suggesting congestion, the number of teenagers with driver’s licenses, and the numbers of miles driven has dropped in recent years, Scientific American asks whether we have reached “peak car”:

According to the Federal Highway Administration’s “2011 Urban Congestion Trends” report, there was a 1.2 percent decline in vehicle miles traveled (VMT) last year compared with 2010. The drop follows years of stagnant growth in vehicle travel following a peak in 2007, before the economic downturn…

Her observation is true for the entire country. Rather than maintain the 50-year legacy of a 2 to 4 percent increase in vehicle travel each year, the annual number of VMT in the United States has stalled and even gone into reverse. The total number of miles driven in the United States today is the same as in 2004…

The interesting thing for Roy Kienitz, transportation infrastructure consultant and former undersecretary for policy at the Department of Transportation, is that American drivers actually started changing their individual driving habits years before the recession started.

The overall number of miles traveled by road peaked just before the market collapsed, but the number of VMT per capita peaked in 2004 and declined over the next eight years until today, according to Kienitz’s research, which is based on publicly available data.

Interesting. But I’m not sure this is the best way to measure “peak car.” While miles driven by road may be important to note, there are other factors that matters. Here are a few:

-The number of vehicles bought.

-The number of vehicles licensed.

-The number or % of people with driver’s licenses.

-The average number of trips people make on a daily basis. This gives you different information than the number of miles driven per year.

-Whether travel by other modes has increased or whether overall miles traveled is down. This would help show whether people are using cars less or really all travel is down.

Looking at all of these figures would help provide a more complete picture of whether we are at “peak car.”

Also, even if Americans are driving less overall, this doesn’t necessarily mean that cars are valued less or are less culturally important. Driving less doesn’t automatically mean most or even a significant number of Americans want to get rid of their cars or the freedom and individualism they represent.

Media looks for ways to better measure fragmented audience

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As media platforms proliferate, media companies are looking for better ways to measure their audience:

“We have Omniture data, comScore, Nielsen, some of our internal metrics that we look at — they don’t match,” Wert said.

Hampering the effort are audiences splintering into ever smaller shards as they use an array of outlets and platforms — including websites, mobile devices, print and broadcast…

The tinier the pieces the more precious each becomes. It’s more important than ever for traditional media looking to cover the costs of producing content to deliver to marketers as much information as possible about who’s watching, reading and listening.

Arguably, technology has made the measurement systems better than ever. But the result is counterintuitive: Consumers are followed more closely but the numbers don’t always add up, and it’s not clear how to put a value on those numbers…

Nielsen’s Patrick Dineen, senior vice president of local television audience measurement, said it’s “wildly inappropriate” to try to track audiences through one medium. Kevin Gallagher, executive vice president and local director at Starcom, said his firm has replaced talk of traditional media planning with something that tracks targeted consumers’ daily interaction with media.

Getting the right numbers means media companies will be able to more accurately gauge advertising, particularly target audiences, and then make more money. Solving these issues and appropriately valuing these media interactions will be a huge issue moving forward and whoever can do it first or do it best could have an advantage.

No agreed-upon standard on how to measure a house’s square footage

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You might think this would have been settled some time ago but apparently not: builders, real estate agents, and assessors do not have a common standard by which to determine the square footage of a house.

Many shoppers blindly trust that the size of a new home featured in an ad or brochure is accurate. But the reality is that no official industry standard exists for calculating residential square footage, nor is there widespread consensus on the correct measuring methodology.

Some builders and agents, for example, tally a home’s total footprint, including uninhabitable space (such as areas between walls), while others round off calculations to the next highest number…

Steve Carr, president of Naperville-based Carr Building and Development LLC, said in new construction the builder or architect usually determines square footage calculations.

For resale homes, square footage is typically determined by the seller’s real estate agent (who will measure the dimensions or obtain predetermined measurements from the county assessor’s office) or by an appraiser, who is enlisted by the seller or, if an appraisal is ordered, the buyer’s lender, Wittman said.

So it sounds like the square footage is determined by whoever has a financial interest in the number. It would be interesting to do a study and look at a sample of homes and see whether the square footage fluctuates depending who is doing the measuring (a buyer, seller, or assessor).

There is some interesting discussion later in the article about how homes cannot strictly be compared on the price per square foot as there are other factors involved. This is true but I think this is misleading: there are few figures that people start with when looking for a home and square footage is one of them (perhaps alongside how many bedrooms the home has). I have thought in the past that people who buy homes for their square footage are different kinds of people (social class, taste) compared to those who buy for the architecture of the home or perhaps the neighborhood.

All together, square footage matters for everyone involved in the building, buying and selling, and taxing of homes and I’m surprised that there is no single standard. Who would lose the most by doing this?

Why two media sources ranking the world’s wealthiest people is a good thing

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While Forbes had the corner on the market for years in compiling a ranking of the world’s richest people, there is now another option: this week Bloomberg released its Billionaires Index. One commentator thinks we don’t need both Forbes and Bloomberg examining this topic:

The Forbes list, available online today, is published every March. (Its companion, the “Forbes 400” list of richest Americans published in September.) It’s hard to not feel that Bloomberg’s outing takes some of the air out of Forbes usually-hyped cover story on who are the world’s richest people. This year’s edition proves unexciting not only because there were few shake-ups in the top spots from 2011’s list, but also because these rankings don’t appear all that different from Bloomberg’s.

Highlights from 2012’s version: With $69 billion, Mexico’s Carlos Slim Helu ranks No. 1 again for the third year in the row. (The magazine also profiled him.) Helu was followed by another 1,225 billionaires, starting with Bill Gates, Warren Buffett, and Bernard Arnault (of Louis Vuitton fame), who were also two through four last year. But beside no one being knocked off the top of this year’s Forbes list, it’s markedly similar to how rich Bloomberg News told us these folks were. Here’s a side-by-side comparison, with Forbes on the left and Bloomberg on the right.

So there are slight differences. Bloomberg has Arnault one spot lower and places fashion mogul Amancio Ortega down to seventh. Bloomberg puts the Koch brothers in the top 10, whereas Forbes had them both pegged at 12th. But isn’t this hair-splitting? If anything, the discrepancies show how hard it is to measure rich people’s riches.

What today’s Forbes list shows more than anything is that we don’t need two billionaires lists reminding us how wealthy the wealthy are. If we had to choose one, we’d go with Bloomberg’s, since it’s updated daily instead of once a year. But we doubt that will stop Forbes from producing its longstanding annual issue as long folks keep buying it.

I disagree. Here is why: I think that having two media sources looking at this topic will actually give readers better information. With two publications tackling the subject, I hope this improves their measurement of wealth for both publications. Perhaps we could average the rankings across the publications to get a more accurate assessment of what is going on. In the end, two sets of people looking at the data is better than one. Because Bloomberg is updating this list daily, perhaps this will push Forbes to update their lists more frequently and move away from a magazine era schedule to an Internet era schedule. The two lists do have some differences and this is not inconsequential. Lots of people are interested in this list and I’m sure some of the people at the top of the list have some interest in where they rank. Of course, these differences can indicate “how hard it is to measure rich people’s riches” but this doesn’t mean we should just throw up our hands and go with one list. Just because these people are really wealthy doesn’t mean that we shouldn’t have more fine-grained analysis of their financial holdings. (This sometimes seems to happen quite a bit in sociology: we assume we know about the elites and so spend more time studying marginalized groups but we have fewer in-depth studies of the elites who do have a lot of influence in society.)

A second issue: Bloomberg obviously thinks there is a market for another list that is updated daily and so this is a market decision as well as a journalistic interest in updating this information more frequently. The Forbes list always gets a lot of attention and Bloomberg probably wants to draw away some of that market. I imagine there is enough room in the market for both lists to survive, particularly as the two could serve different markets. However, it will be interesting to see how the rest of the media responds to changes in the Bloomberg list: if someone moves up from #3 to #2 in the next few days, will there be news stories about it? Will journalists providing background information about the wealthy reference the Forbes or the Bloomberg list?

A new statistic to measure chemistry in basketball

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Team chemistry is an elusive concept to measure but three “quantitative traders in the financial world” have developed a new statistic they say tackles the subject:

We introduce a novel Skills Plus Minus (“SPM”) framework to measure on-court chemistry in basketball. First, we evaluate each player’s offense and defense in the SPM framework based on three basic categories of skills: scoring, rebounding, and ball-handling. We then simulate games using the skill ratings of the ten players on the court. The results of the simulations measure the effectiveness of individual players as well as the 5-player lineup, so we can then calculate the synergies of each NBA team by comparing their 5-player lineup’s effectiveness to the “sum-of-the-parts.” We find that these synergies can be large and meaningful. Because skills have different synergies with other skills, our framework predicts that a player’s value is dependent on the other nine players on the court. Therefore, the desirability of a free agent depends on the players currently on the roster. Indeed, our framework is able to generate mutually beneficial trades between teams…

The research team pored over a ton of data, ran countless simulations and looked at how many points certain combinations of skills created…

One pattern that emerged was that “rare events” (like steals/defensive ball-handling) tended to produce positive synergies, while “common events” (like defensive rebounds) produce negative synergies. How come? Because increasing a team’s rebounding rate from 70 percent of defensive rebounds (which would be lousy) to, say, 75 percent (very good) represents only a 7 percent increase. But upping offensive rebounds, which aren’t nearly as common as defensive rebounds, from a rate of 30 percent to 35 percent represents a robust 17 percent gain…

Figuring out the component parts of what we know as chemistry or synergy is one of the next great frontiers of this movement. It’s not enough to put an exceptional distributor on the floor. To maximize that point guard’s gifts, a team must surround him with the right combination of players — and that combination might not always be the sexiest free agents on the market.

Sports has so much data to pore over that researchers could be occupied with for a long time.

This particular question is fascinating because one could get a lot of answers to why certain five player units are successful from different actors such as coaches, players, commentators, and fans. Players might be easier to assess (ha – look at all the issues with drafting) but looking at units requires sharp analytical skills and an overall view of a team.

Which team(s) will be the first to utilize this statistic and really build team units rather than cobble together a number of good players and then try to squeeze the best out of them? Certain players who might be considered “busts” may simply be in the wrong systems and be the “missing piece” for another team.

Measuring faculty productivity in sociology

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A sociologist and associate dean at the University of Texas-Austin has recently put together a report on faculty productivity at his school that was undertaken to counter criticism that some faculty at the school didn’t do enough research to justify the money paid by taxpayers to support the school. The report cautions against using the same measures of productivity across disciplines:

While Musick said there was value in using the available numbers on research support, he stressed the importance of recognizing that this is valid only for some disciplines. (And one of his recommendations going forward is that the university develop better measures for research productivity of faculty members who work in disciplines without significant sources of outside funding.)

His own field of sociology is a perfect illustration of the limits of using outside funding as a measure of faculty research productivity, Musick said. Sociologists have some government support for which they can apply, but not nearly as much as do those in the physical or biological sciences, he noted. Even within fields, one’s success at obtaining funds may be based on area of expertise, not productivity. Musick said that as a medical sociologist, he has been able to win National Institutes of Health grants that some of his colleagues in sociology — people with good research agendas — could not seek.

He also said it was important to reject the idea that universities should be based only upon those fields that can attract the most outside support — even if you have a goal of producing more scientists. Musick cited as examples STEM-oriented universities such as the Massachusetts Institute of Technology and the California Institute of Technology — both of which invest significant funds in humanities and social science programs. “They recognize that universities are ecosystems,” he said. “They recognize that to produce the best scientists, they need the humanities and social sciences and the fine arts.”

It would also be helpful to keep in mind that there is even disagreement within sociology about faculty productivity. (I assume these discussions might also take place within other disciplines.) I’ve seen some heated discussion between faculty of different subfields of sociology where productivity is measured in very different ways. A book might be considered a massive achievement in one subfield while multiple journal articles are the norm in another. Plus, you could get into the quality of such publications which can also be difficult to assess. Impact factor seems to be the favored way to do this today but that has some issues and applies only to journal articles. Additionally, we could ask what the benchmark for overall productivity is: should UT-Austin match other R1 public schools and/or places like Harvard and Princeton?

Does the availability of outside funding help explain why medical sociology is a growing subfield?

An emerging portrait of emerging adults in the news, part 3

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In recent weeks, a number of studies have been reported on that discuss the beliefs and behaviors of the younger generation, those who are now between high school and age 30 (an age group that could also be labeled “emerging adults”). In a three-part series, I want to highlight three of these studies because they not only suggest what this group is doing but also hints at the consequences. A study in part one showed that there is an association between hyper-texting and hyper social networking use and risky behavior. A study in part two showed that teens and college students today are more tolerant than previous generations but less empathetic.

Another interesting aspect of the lives of emerging adults is living alone. While this is common among the middle-aged, the proportion of emerging adults living alone is growing:

The stats are arresting. In this country, approximately 31 million people live alone, and one-person households make up 28 percent of the total, tying with childless couples as the most common residential type — “more common,’’ Klinenberg pointed out, “than the nuclear family, the multigenerational family, and the roommate or group home.’’

Those who live alone are mostly middle-age, with young adults the fastest-growing segment, and there are more women than men. No longer a transitional stage, living alone is one of the most stable household arrangements. And while one-person households were once scattered in low-density rural settings, they’re now concentrated in cities. “In Manhattan,’’ he said, “more than half of all residences are one-person dwellings.’’

I’ve seen a number of commentators attempt explanations for this: this is part of becoming an adult today, television shows like Friends or How I Met Your Mother glamorized the social life in the city (though these shows tend to show roommates living together), outrageous housing costs push younger people into odd living arrangements.

But couldn’t this trend toward living alone be linked to the two prior studies we looked at? If a lot of social life occurs through texting or through social networking sites and emerging adults are more tolerant but less empathetic, then living alone makes some sense. Emerging adults still have a social life – but this social life may look quite different as friends are found and communicated with through technology or social outings rather than through closer ties (such as living together).

And what if living alone or being alone more is the outcome for younger generations? How might this impact society? Such arrangements may be good for self-actualization (or not) but there will be consequences. What will “community” look like in several decades? If these three studies were all the evidence we had, we might conclude that emerging adults like to be social but also like to keep people at an arm’s length.

It is hard to draw conclusions from three studies that are reported in the news – but here is the emerging portrait: social interaction is changing. It may be easy to dismiss this new interaction as bad or wrong but we need more information and research on this particular topic. We need more measurement of depth or quality of relationships. Out of these three studies, we have two measures of interaction quality: the prevalence of risky behaviors (though this is only an association or correlation) and levels of empathy. We could be asking other questions like how many students in college today make arrangements for single rooms in dorms or would prefer to live in single rooms? How many students who study abroad actually are able to fully understand and appreciate a new culture versus just being able to see the differences two cultures?

All of this will be interesting to watch in the coming years as emerging adults  obtain the power to shape society’s values regarding interaction and community.

Disagreement about unemployment figures between government and Gallup

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Gallup suggests that the unemployment figures to be released by the federal government at the end of this week are underestimates. While the government figures are expected to be around 9.6-9.8%, Gallup says the unemployment is really closer to 10.1%.

The main issue seems to be that Gallup is measuring through the end of September while the government figures are based on data that ended in mid-September. And Gallup found that unemployment increased quite a bit in the last few weeks of September.

On list of generous nations, US ranks 5th

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Gallup has released “The World Giving Index 2010” and the United States is tied for fifth with Switzerland and behind Australia and New Zealand (tied for first) and Ireland and Canada (tied for third).

It looks like respondents were asked whether they did three things within the past month: gave money to an organization, volunteered for an organization, or helped someone they didn’t know.

Gallup suggests “the level of satisfaction or happiness of the population is emerging as the key driver for increasing the giving of money.” They also argue there could be “a positive cycle of giving” where happier people give to others who then are more likely to give.

I would be interested to know how much a country’s culture affects this. Are there certain societal traits that lead to more giving? Or are there certain economic and governmental structures that encourage more giving?