andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2308 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i.e., opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. Yet, I never could find anyone who had the same remembrance (or interest in the topic). The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U.S. from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. In 1958, the U.S. Bureau of Public Roads adopted white as the standard color for the new interstate highway system. The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color o
sentIndex sentText sentNum sentScore
1 Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i. [sent-1, score-0.713]
2 , opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. [sent-3, score-1.148]
3 Yet, I never could find anyone who had the same remembrance (or interest in the topic). [sent-4, score-0.075]
4 The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U. [sent-5, score-0.059]
5 from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. [sent-7, score-1.159]
6 By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. [sent-8, score-1.159]
7 Bureau of Public Roads adopted white as the standard color for the new interstate highway system. [sent-11, score-1.165]
8 The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color of center lines nationwide. [sent-12, score-1.297]
9 The changeover to the 1971 MUTCD standards took place between 1971 and 1975, with most done by the end of 1973, so for two years drivers still had to use the old and new. [sent-13, score-0.185]
10 Yellow was adopted because it was already the standard color of warning signs, and because it was easy to teach drivers to associate yellow lines with dividing opposing traffic and white lines with dividing traffic in the same direction. [sent-14, score-2.707]
11 Most European countries reserve white for routine lane markings of any kind. [sent-18, score-0.41]
12 Yellow is used to mark forbidden parking, such as on bus stops. [sent-19, score-0.132]
13 Most countries in North and South America have yellow lines separating traffic directions. [sent-20, score-0.915]
14 Armed with this knowledge, I have haphazardly been asking (annoying) American friends and relations as to what color they think the center line is now, let alone what it used to be. [sent-22, score-0.87]
15 Young people get it right I guess because that is part of driver ed which they have recently completed; older people who drive a lot still claim the center line is white and always has been. [sent-23, score-0.684]
16 Alper continues: If in fact so many Americans do not recall such an everyday occurrence what does this say about self-reporting and eye-witness testimony—like the famous gorillas across the screen in that classic psych study? [sent-28, score-0.192]
17 So, as a simple experiment is there a way of improving my haphazard sampling to give some statistical “oomph” to the contention that (older? [sent-29, score-0.14]
18 Redo the gorilla example by changing the color of the center line every few seconds while focusing attention on other aspects of driving? [sent-31, score-0.954]
19 Does inattentiveness to color of the dividing line correlate with age, gender, handedness, SAT math score, religion, Vitamin D consumption, etc. [sent-32, score-0.83]
20 If you want to maximize your chances of getting it into Psychological Science, do several experiments, each with a nice small sample size—25 or 50 in each case should do it—and keep all your data-analysis options open . [sent-36, score-0.056]
wordName wordTfidf (topN-words)
[('color', 0.425), ('yellow', 0.325), ('traffic', 0.283), ('white', 0.219), ('center', 0.213), ('highway', 0.189), ('alper', 0.184), ('dividing', 0.18), ('adopted', 0.173), ('lines', 0.17), ('line', 0.162), ('opposing', 0.103), ('drivers', 0.102), ('standard', 0.094), ('older', 0.09), ('standards', 0.083), ('changing', 0.079), ('remembrance', 0.075), ('forbidden', 0.075), ('gorilla', 0.075), ('countries', 0.074), ('chile', 0.07), ('haphazardly', 0.07), ('mandated', 0.07), ('haphazard', 0.07), ('contention', 0.07), ('gorillas', 0.07), ('handedness', 0.067), ('firmly', 0.065), ('interstate', 0.065), ('redo', 0.065), ('obsessed', 0.065), ('armed', 0.065), ('occurrence', 0.063), ('separating', 0.063), ('correlate', 0.063), ('testimony', 0.063), ('vitamin', 0.063), ('oregon', 0.061), ('divides', 0.061), ('states', 0.059), ('lane', 0.059), ('psych', 0.059), ('continuously', 0.059), ('reserve', 0.058), ('roads', 0.058), ('manual', 0.058), ('bus', 0.057), ('devices', 0.057), ('maximize', 0.056)]
simIndex simValue blogId blogTitle
same-blog 1 1.0000002 2308 andrew gelman stats-2014-04-27-White stripes and dead armadillos
Introduction: Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i.e., opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. Yet, I never could find anyone who had the same remembrance (or interest in the topic). The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U.S. from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. In 1958, the U.S. Bureau of Public Roads adopted white as the standard color for the new interstate highway system. The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color o
2 0.15760669 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year
Introduction: Under the subject line “Blog bait!”, Brendan Nyhan points me to this post at the Washington Post blog: For 2013, we asked some of the year’s most interesting, important and influential thinkers to name their favorite graph of the year — and why they chose it. Here’s Bill Gates’s. Infographic by Thomas Porostocky for WIRED. “I love this graph because it shows that while the number of people dying from communicable diseases is still far too high, those numbers continue to come down. . . .” As Brendan is aware, this is not my favorite sort of graph, it’s a bit of a puzzle to read and figure out where all the pieces fit in, also weird stuff going on like 3-D effects and the big space taken up by those yellow and green borders, as well as tricky things like understanding what some of those little blocks are, and perhaps the biggest question, what is the definition of an “untimely death.” But, as often is the case, the defects of the graph form a statistical perspective can
Introduction: Sandeep Baliga writes : [In a recent study , Gilles Duranton and Matthew Turner write:] For interstate highways in metropolitan areas we [Duranton and Turner] find that VKT (vehicle kilometers traveled) increases one for one with interstate highways, confirming the fundamental law of highway congestion.’ Provision of public transit also simply leads to the people taking public transport being replaced by drivers on the road. Therefore: These findings suggest that both road capacity expansions and extensions to public transit are not appropriate policies with which to combat traffic congestion. This leaves congestion pricing as the main candidate tool to curb traffic congestion. To which I reply: Sure, if your goal is to curb traffic congestion . But what sort of goal is that? Thinking like a microeconomist, my policy goal is to increase people’s utility. Sure, traffic congestion is annoying, but there must be some advantages to driving on that crowded road or pe
Introduction: As I’ve written here many times, my experiences in social science and public health research have left me skeptical of statistical methods that hypothesize or try to detect zero relationships between observational data (see, for example, the discussion starting at the bottom of page 960 in my review of causal inference in the American Journal of Sociology). In short, I have a taste for continuous rather than discrete models. As discussed in the above-linked article (with respect to the writings of cognitive scientist Steven Sloman), I think that common-sense thinking about causal inference can often mislead. In many cases, I have found that that the theoretical frameworks of instrumental variables and potential outcomes (for a review see, for example, chapters 9 and 10 of my book with Jennifer) help clarify my thinking. Here is an example that came up in a recent blog discussion. Computer science student Elias Bareinboim gave the following example: “suppose we know nothing a
5 0.11606965 1316 andrew gelman stats-2012-05-12-black and Black, white and White
Introduction: I’ve always thought it looked strange to see people referred to in print as Black or White rather than black or white. For example consider this sentence: “A black guy was walking down the street and he saw a bunch of white guys standing around.” That looks fine, whereas “A Black guy was walking down the street and he saw a bunch of White guys standing around”—that looks weird to me, as if the encounter was taking place in an Ethnic Studies seminar. But maybe I’m wrong on this. Jay Livingston argues that black and white are colors whereas Black and White are races (or, as I would prefer to say, ethnic categories) and illustrates with this picture of a white person and a White person: In conversation, I sometimes talk about pink people, brown people, and tan people, but that won’t work in a research paper. P.S. I suspect Carp will argue that I’m being naive: meanings of words change across contexts and over time. To which I reply: Sure, but I still have to choose h
6 0.11519343 502 andrew gelman stats-2011-01-04-Cash in, cash out graph
7 0.11199505 161 andrew gelman stats-2010-07-24-Differences in color perception by sex, also the Bechdel test for women in movies
8 0.097033143 1452 andrew gelman stats-2012-08-09-Visually weighting regression displays
9 0.096371144 1064 andrew gelman stats-2011-12-16-The benefit of the continuous color scale
10 0.096212842 752 andrew gelman stats-2011-06-08-Traffic Prediction
11 0.089941971 2288 andrew gelman stats-2014-04-10-Small multiples of lineplots > maps (ok, not always, but yes in this case)
12 0.088447481 2255 andrew gelman stats-2014-03-19-How Americans vote
13 0.086983785 1478 andrew gelman stats-2012-08-31-Watercolor regression
14 0.086777933 943 andrew gelman stats-2011-10-04-Flip it around
15 0.086293615 428 andrew gelman stats-2010-11-24-Flawed visualization of U.S. voting maybe has some good features
16 0.086156093 1684 andrew gelman stats-2013-01-20-Ugly ugly ugly
17 0.083121307 2038 andrew gelman stats-2013-09-25-Great graphs of names
18 0.081832953 422 andrew gelman stats-2010-11-20-A Gapminder-like data visualization package
19 0.081623375 832 andrew gelman stats-2011-07-31-Even a good data display can sometimes be improved
20 0.078653805 252 andrew gelman stats-2010-09-02-R needs a good function to make line plots
topicId topicWeight
[(0, 0.12), (1, -0.046), (2, 0.039), (3, 0.009), (4, 0.051), (5, -0.023), (6, -0.023), (7, 0.02), (8, -0.026), (9, 0.009), (10, -0.027), (11, -0.017), (12, 0.016), (13, 0.041), (14, 0.015), (15, 0.009), (16, 0.053), (17, -0.004), (18, 0.02), (19, -0.03), (20, 0.004), (21, 0.006), (22, -0.01), (23, -0.002), (24, 0.018), (25, -0.017), (26, 0.0), (27, 0.004), (28, 0.031), (29, 0.033), (30, 0.033), (31, -0.027), (32, -0.047), (33, -0.016), (34, -0.006), (35, -0.04), (36, 0.008), (37, 0.027), (38, -0.008), (39, 0.024), (40, -0.041), (41, 0.0), (42, 0.016), (43, 0.03), (44, -0.004), (45, 0.019), (46, 0.003), (47, 0.017), (48, 0.012), (49, -0.023)]
simIndex simValue blogId blogTitle
same-blog 1 0.95640063 2308 andrew gelman stats-2014-04-27-White stripes and dead armadillos
Introduction: Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i.e., opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. Yet, I never could find anyone who had the same remembrance (or interest in the topic). The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U.S. from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. In 1958, the U.S. Bureau of Public Roads adopted white as the standard color for the new interstate highway system. The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color o
Introduction: Aleks points me to this article showing some pretty maps by Eric Fisher showing where people of different ethnicity live within several metro areas within the U.S. The idea is simple but effective; in the words of Cliff Kuang: Fisher used a straight forward method borrowed from Rankin: Using U.S. Census data from 2000, he created a map where one dot equals 25 people. The dots are then color-coded based on race: White is pink; Black is blue; Hispanic is orange, and Asian is green. The results for various cities are fascinating: Just like every city is different, every city is integrated (or segregated) in different ways. New York is shown below. No, San Francisco is not “very, very white” But I worry that these maps are difficult for non-experts to read. For example, Kuang writes the following:: San Francisco proper is very, very white. This is an understandable mistake coming from someone who, I assume, has never lived in the Bay Area. But what’s amazing i
3 0.73149329 1498 andrew gelman stats-2012-09-16-Choices in graphing parallel time series
Introduction: I saw this graph posted by Tyler Cowen: and my first thought was that the bar plot should be replaced by a line plot: Six lines, one for each income category, with each line being a time series of these changes. With a line plot, you can more easily see each time series (these are hard to see in the barplot because you have to follow each color and jump from decade to decade) and also compare the patterns for each category. The line plot pretty much dominates the bar plot. At least that was the theory. Now here’s what actually happened. I downloaded the data as Excel files, saved them as csv, then read them into R. In all, it took close to an hour to get the data set up in the format that was needed to make the graphs. At this point it was pretty easy to make the line plot. But the result was disappointing: The six lines are hard to untangle (sure, a better color scheme might help, but it wouldn’t really solve the problem) and the graph as a whole is much l
4 0.73112392 1386 andrew gelman stats-2012-06-21-Belief in hell is associated with lower crime rates
Introduction: I remember attending a talk a few years ago by my political science colleague John Huber in which he discussed cross-national comparisons of religious attitudes. One thing I remember is that the U.S. is highly religious, another thing I remembered is that lots more Americans believe in heaven than believe in hell. Some of this went into Red State Blue State—not the heaven/hell thing, but the graph of religiosity vs. GDP: and the corresponding graph of religious attendance vs. GDP for U.S. states: Also we learned that, at the individual level, the correlation of religious attendance with income is zero (according to survey reports, rich Americans are neither more nor less likely than poor Americans to go to church regularly): while the correlation of prayer with income is strongly negative (poor Americans are much more likely than rich Americans to regularly pray): Anyway, with all this, I was primed to be interested in a recent study by psychologist
5 0.72790051 915 andrew gelman stats-2011-09-17-(Worst) graph of the year
Introduction: This (forwarded to me from Jeff, from a powerpoint by Willam Gawthrop) wins not on form but on content: Really this graph should stand alone but it’s so wonderful that I can’t resist pointing out a few things: - The gap between 610 and 622 A.D. seems to be about the same as the previous 600 years, and only a little less than the 1400 years before that. - “Pious and devout” Jews are portrayed as having steadily increased in nonviolence up to the present day. Been to Israel lately? - I assume the line labeled “Bible” is referring to Christians? I’m sort of amazed to see pious and devout Christians listed as being maximally violent at the beginning. Huh? I thought Christ was supposed to be a nonviolent, mellow dude. The line starts at 3 B.C., implying that baby Jesus was at the extreme of violence. Gong forward, we can learn from the graph that pious and devout Christians in 1492 or 1618, say, were much more peaceful than Jesus and his crew. - Most amusingly g
6 0.72584009 672 andrew gelman stats-2011-04-20-The R code for those time-use graphs
7 0.7164641 469 andrew gelman stats-2010-12-16-2500 people living in a park in Chicago?
8 0.71164101 12 andrew gelman stats-2010-04-30-More on problems with surveys estimating deaths in war zones
9 0.7103126 1669 andrew gelman stats-2013-01-12-The power of the puzzlegraph
10 0.69519776 787 andrew gelman stats-2011-07-05-Different goals, different looks: Infovis and the Chris Rock effect
11 0.67988527 670 andrew gelman stats-2011-04-20-Attractive but hard-to-read graph could be made much much better
12 0.67808104 1342 andrew gelman stats-2012-05-24-The Used TV Price is Too Damn High
13 0.6752125 536 andrew gelman stats-2011-01-24-Trends in partisanship by state
14 0.67415905 489 andrew gelman stats-2010-12-28-Brow inflation
15 0.66567945 1316 andrew gelman stats-2012-05-12-black and Black, white and White
16 0.66213864 2203 andrew gelman stats-2014-02-08-“Guys who do more housework get less sex”
18 0.65844464 502 andrew gelman stats-2011-01-04-Cash in, cash out graph
19 0.65753114 2288 andrew gelman stats-2014-04-10-Small multiples of lineplots > maps (ok, not always, but yes in this case)
20 0.65544146 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year
topicId topicWeight
[(6, 0.022), (16, 0.074), (24, 0.128), (30, 0.013), (31, 0.057), (36, 0.025), (57, 0.026), (63, 0.05), (66, 0.043), (71, 0.031), (72, 0.066), (76, 0.047), (95, 0.093), (99, 0.191)]
simIndex simValue blogId blogTitle
same-blog 1 0.94772029 2308 andrew gelman stats-2014-04-27-White stripes and dead armadillos
Introduction: Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i.e., opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. Yet, I never could find anyone who had the same remembrance (or interest in the topic). The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U.S. from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. In 1958, the U.S. Bureau of Public Roads adopted white as the standard color for the new interstate highway system. The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color o
Introduction: Mike Spagat sent me an email with the above heading, referring to this paper by Leontine Alkema and Jin Rou New, which begins: National estimates of the under-5 mortality rate (U5MR) are used to track progress in reducing child mortality and to evaluate countries’ performance related to United Nations Millennium Development Goal 4, which calls for a reduction in the U5MR by two-thirds between 1990 and 2015. However, for the great majority of developing countries without well-functioning vital registration systems, estimating levels and trends in child mortality is challenging, not only because of limited data availability but also because of issues with data quality. Global U5MR estimates are often constructed without accounting for potential biases in data series, which may lead to inaccurate point estimates and/or credible intervals. We describe a Bayesian penalized B-spline regression model for assessing levels and trends in the U5MR for all countries in the world, whereby bi
3 0.88113487 1164 andrew gelman stats-2012-02-13-Help with this problem, win valuable prizes
Introduction: Corrected equation This post is by Phil. In the comments to an earlier post , I mentioned a problem I am struggling with right now. Several people mentioned having (and solving!) similar problems in the past, so this seems like a great way for me and a bunch of other blog readers to learn something. I will describe the problem, one or more of you will tell me how to solve it, and you will win…wait for it….my thanks, and the approval and admiration of your fellow blog readers, and a big thank-you in any publication that includes results from fitting the model. You can’t ask fairer than that! Here’s the problem. The goal is to estimate six parameters that characterize the leakiness (or air-tightness) of a house with an attached garage. We are specifically interested in the parameters that describe the connection between the house and the garage; this is of interest because of the effect on the air quality in the house if there are toxic chemic
4 0.88073707 266 andrew gelman stats-2010-09-09-The future of R
Introduction: Some thoughts from Christian , including this bit: We need to consider separately 1. R’s brilliant library 2. R’s not-so-brilliant language and/or interpreter. I don’t know that R’s library is so brilliant as all that–if necessary, I don’t think it would be hard to reprogram the important packages in a new language. I would say, though, that the problems with R are not just in the technical details of the language. I think the culture of R has some problems too. As I’ve written before, R functions used to be lean and mean, and now they’re full of exception-handling and calls to other packages. R functions are spaghetti-like messes of connections in which I keep expecting to run into syntax like “GOTO 120.” I learned about these problems a couple years ago when writing bayesglm(), which is a simple adaptation of glm(). But glm(), and its workhorse, glm.fit(), are a mess: They’re about 10 lines of functioning code, plus about 20 lines of necessary front-end, plus a cou
5 0.87582493 12 andrew gelman stats-2010-04-30-More on problems with surveys estimating deaths in war zones
Introduction: Andrew Mack writes: There was a brief commentary from the Benetech folk on the Human Security Report Project’s, “The Shrinking Costs of War” report on your blog in January. But the report has since generated a lot of public controversy . Since the report–like the current discussion in your blog on Mike Spagat’s new paper on Iraq–deals with controversies generated by survey-based excess death estimates, we thought your readers might be interested. Our responses to the debate were posted on our website last week. “Shrinking Costs” had discussed the dramatic decline in death tolls from wartime violence since the end of World War II –and its causes. We also argued that deaths from war-exacerbated disease and malnutrition had declined. (The exec. summary is here .) One of the most striking findings was that mortality rates (we used under-five mortality data) decline during most wars. Indeed our latest research indicates that of the total number of years that countries w
6 0.87326056 599 andrew gelman stats-2011-03-03-Two interesting posts elsewhere on graphics
8 0.87084162 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year
10 0.86295217 1070 andrew gelman stats-2011-12-19-The scope for snooping
11 0.85990894 1973 andrew gelman stats-2013-08-08-For chrissake, just make up an analysis already! We have a lab here to run, y’know?
12 0.85935175 1086 andrew gelman stats-2011-12-27-The most dangerous jobs in America
13 0.85830653 2288 andrew gelman stats-2014-04-10-Small multiples of lineplots > maps (ok, not always, but yes in this case)
14 0.85739791 829 andrew gelman stats-2011-07-29-Infovis vs. statgraphics: A clear example of their different goals
15 0.85399854 1737 andrew gelman stats-2013-02-25-Correlation of 1 . . . too good to be true?
16 0.85210454 1595 andrew gelman stats-2012-11-28-Should Harvard start admitting kids at random?
17 0.85108429 624 andrew gelman stats-2011-03-22-A question about the economic benefits of universities
18 0.84840608 1575 andrew gelman stats-2012-11-12-Thinking like a statistician (continuously) rather than like a civilian (discretely)
19 0.84738886 519 andrew gelman stats-2011-01-16-Update on the generalized method of moments
20 0.84690547 1646 andrew gelman stats-2013-01-01-Back when fifty years was a long time ago