andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-549 knowledge-graph by maker-knowledge-mining

549 andrew gelman stats-2011-02-01-“Roughly 90% of the increase in . . .” Hey, wait a minute!


meta infos for this blog

Source: html

Introduction: Matthew Yglesias links approvingly to the following statement by Michael Mandel: Homeland Security accounts for roughly 90% of the increase in federal regulatory employment over the past ten years. Roughly 90%, huh? That sounds pretty impressive. But wait a minute . . . what if total federal regulatory employment had increased a bit less. Then Homeland Security could’ve accounted for 105% of the increase, or 500% of the increase, or whatever. The point is the change in total employment is the sum of a bunch of pluses and minuses. It happens that, if you don’t count Homeland Security, the total hasn’t changed much–I’m assuming Mandel’s numbers are correct here–and that could be interesting. The “roughly 90%” figure is misleading because, when written as a percent of the total increase, it’s natural to quickly envision it as a percentage that is bounded by 100%. There is a total increase in regulatory employment that the individual agencies sum to, but some margins are p


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Matthew Yglesias links approvingly to the following statement by Michael Mandel: Homeland Security accounts for roughly 90% of the increase in federal regulatory employment over the past ten years. [sent-1, score-1.187]

2 what if total federal regulatory employment had increased a bit less. [sent-7, score-0.995]

3 Then Homeland Security could’ve accounted for 105% of the increase, or 500% of the increase, or whatever. [sent-8, score-0.069]

4 The point is the change in total employment is the sum of a bunch of pluses and minuses. [sent-9, score-0.903]

5 It happens that, if you don’t count Homeland Security, the total hasn’t changed much–I’m assuming Mandel’s numbers are correct here–and that could be interesting. [sent-10, score-0.429]

6 The “roughly 90%” figure is misleading because, when written as a percent of the total increase, it’s natural to quickly envision it as a percentage that is bounded by 100%. [sent-11, score-0.442]

7 There is a total increase in regulatory employment that the individual agencies sum to, but some margins are positive and some are negative. [sent-12, score-1.767]

8 If the total happens to be near zero, then the individual pieces can appear to be large fractions of the total, even possibly over 100%. [sent-13, score-0.637]

9 I’m not saying that Mandel made any mistakes, just that, in general, ratios can be tricky when the denominator is the sum of positive and negative parts. [sent-14, score-0.909]

10 In this particular case, the margins were large but not quite over 100%, which somehow gives the comparison more punch than it deserves, I think. [sent-15, score-0.281]

11 We discussed a mathematically identical case a few years ago involving the 2008 Democratic primary election campaign. [sent-16, score-0.174]

12 The funny thing is that the denominator has to be small (so that the numerator seems like a lot, “90%” or whatever) but not too small (because if the ratio is over 100%, the jig is up). [sent-20, score-0.498]

13 Mandel replies that, yes, he agrees with me in general about the problems of ratios where the denominator is a sum of positive and negative components, but that in this particular case, “all the major components of regulatory employment change are either positive or a very tiny negative. [sent-23, score-1.952]

14 ” So it sounds like I was choosing a bad example to make my point! [sent-24, score-0.138]


similar blogs computed by tfidf model

tfidf for this blog:

wordName wordTfidf (topN-words)

[('mandel', 0.369), ('total', 0.299), ('regulatory', 0.296), ('employment', 0.296), ('denominator', 0.257), ('homeland', 0.249), ('sum', 0.244), ('increase', 0.198), ('security', 0.171), ('margins', 0.152), ('roughly', 0.146), ('positive', 0.145), ('ratios', 0.119), ('components', 0.119), ('federal', 0.104), ('misplaced', 0.087), ('approvingly', 0.083), ('fractions', 0.083), ('sounds', 0.082), ('negative', 0.08), ('happens', 0.079), ('numerator', 0.076), ('envision', 0.076), ('punch', 0.074), ('agencies', 0.069), ('yglesias', 0.069), ('accounted', 0.069), ('individual', 0.068), ('bounded', 0.067), ('agrees', 0.065), ('minute', 0.064), ('tricky', 0.064), ('accounts', 0.064), ('deserves', 0.064), ('change', 0.064), ('replies', 0.063), ('fallacy', 0.06), ('mathematically', 0.06), ('case', 0.059), ('tiny', 0.059), ('matthew', 0.057), ('hasn', 0.056), ('choosing', 0.056), ('identical', 0.055), ('ratio', 0.055), ('large', 0.055), ('small', 0.055), ('wait', 0.055), ('pieces', 0.053), ('count', 0.051)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 1.0000002 549 andrew gelman stats-2011-02-01-“Roughly 90% of the increase in . . .” Hey, wait a minute!

Introduction: Matthew Yglesias links approvingly to the following statement by Michael Mandel: Homeland Security accounts for roughly 90% of the increase in federal regulatory employment over the past ten years. Roughly 90%, huh? That sounds pretty impressive. But wait a minute . . . what if total federal regulatory employment had increased a bit less. Then Homeland Security could’ve accounted for 105% of the increase, or 500% of the increase, or whatever. The point is the change in total employment is the sum of a bunch of pluses and minuses. It happens that, if you don’t count Homeland Security, the total hasn’t changed much–I’m assuming Mandel’s numbers are correct here–and that could be interesting. The “roughly 90%” figure is misleading because, when written as a percent of the total increase, it’s natural to quickly envision it as a percentage that is bounded by 100%. There is a total increase in regulatory employment that the individual agencies sum to, but some margins are p

2 0.13855661 2287 andrew gelman stats-2014-04-09-Advice: positive-sum, zero-sum, or negative-sum

Introduction: There’s a lot of free advice out there. I offer some of it myself! As I’ve written before (see this post from 2008 reacting to this advice from Dan Goldstein for business school students, and this post from 2010 reacting to some general advice from Nassim Taleb), what we see is typically presented as advice to individuals, but it’s also interesting to consider the possible total effects if the advice is taken. It’s time to play the game again. This time it’s advice from sociologist Fabio Rojas for Ph.D. students. I’ll copy his eight points of advice, then, for each, evaluate whether I think it is positive or negative sum: 1. Show up. Even if you feel horrible, show up. No matter what. Period. Unless someone died in your family, show up. 2. Do your job. Grade the papers. Do the lab work. Unless the work is extreme, take it in stride. 3. Be completely realistic about how you will be evaluated from day #1 – acquire a teaching record and a record of publication. Don’t h

3 0.12864 248 andrew gelman stats-2010-09-01-Ratios where the numerator and denominator both change signs

Introduction: A couple years ago, I used a question by Benjamin Kay as an excuse to write that it’s usually a bad idea to study a ratio whose denominator has uncertain sign. As I wrote then: Similar problems arise with marginal cost-benefit ratios, LD50 in logistic regression (see chapter 3 of Bayesian Data Analysis for an example), instrumental variables, and the Fieller-Creasy problem in theoretical statistics. . . . In general, the story is that the ratio completely changes in interpretation when the denominator changes sign. More recently, Kay sent in a related question: I [Kay] wondered if you have any advice on handling ratios when the signs change as a result of a parameter. I have three functions, one C * x^a, another D * x^a, and a third f(x,a) in my paper such that: C * x^a, < f(x,a) < D * x^a C,D and a all have the same signs. We can divide through by C * x^a but the results depend on the sign of C either 1< f(x,a) / C * x^a < D * x^a / C * x^a, or 1 / f(x,a

4 0.11811539 447 andrew gelman stats-2010-12-03-Reinventing the wheel, only more so.

Introduction: Posted by Phil Price: A blogger (can’t find his name anywhere on his blog) points to an article in the medical literature in 1994 that is…well, it’s shocking, is what it is. This is from the abstract: In Tai’s Model, the total area under a curve is computed by dividing the area under the curve between two designated values on the X-axis (abscissas) into small segments (rectangles and triangles) whose areas can be accurately calculated from their respective geometrical formulas. The total sum of these individual areas thus represents the total area under the curve. Validity of the model is established by comparing total areas obtained from this model to these same areas obtained from graphic method (less than +/- 0.4%). Other formulas widely applied by researchers under- or overestimated total area under a metabolic curve by a great margin Yes, that’s right, this guy has rediscovered the trapezoidal rule. You know, that thing most readers of this blog were taught back in 1

5 0.1143937 1086 andrew gelman stats-2011-12-27-The most dangerous jobs in America

Introduction: Robin Hanson writes: On the criteria of potential to help people avoid death, this would seem to be among the most important news I’ve ever heard. [In his recent Ph.D. thesis , Ken Lee finds that] death rates depend on job details more than on race, gender, marriage status, rural vs. urban, education, and income  combined !  Now for the details. The US Department of Labor has described each of 807 occupations with over 200 detailed features on how jobs are done, skills required, etc.. Lee looked at seven domains of such features, each containing 16 to 57 features, and for each domain Lee did a factor analysis of those features to find the top 2-4 factors. This gave Lee a total of 22 domain factors. Lee also found four overall factors to describe his total set of 225 job and 9 demographic features. (These four factors explain 32%, 15%, 7%, and 4% of total variance.) Lee then tried to use these 26 job factors, along with his other standard predictors (age, race, gender, m

6 0.10833534 1346 andrew gelman stats-2012-05-27-Average predictive comparisons when changing a pair of variables

7 0.10400849 645 andrew gelman stats-2011-04-04-Do you have any idea what you’re talking about?

8 0.10004374 108 andrew gelman stats-2010-06-24-Sometimes the raw numbers are better than a percentage

9 0.09672191 775 andrew gelman stats-2011-06-21-Fundamental difficulty of inference for a ratio when the denominator could be positive or negative

10 0.095859416 1503 andrew gelman stats-2012-09-19-“Poor Smokers in New York State Spend 25% of Income on Cigarettes, Study Finds”

11 0.089308999 712 andrew gelman stats-2011-05-14-The joys of working in the public domain

12 0.081321359 1730 andrew gelman stats-2013-02-20-Unz on Unz

13 0.079377592 1761 andrew gelman stats-2013-03-13-Lame Statistics Patents

14 0.075527102 63 andrew gelman stats-2010-06-02-The problem of overestimation of group-level variance parameters

15 0.075286902 660 andrew gelman stats-2011-04-14-Job opening at NIH for an experienced statistician

16 0.075071447 2194 andrew gelman stats-2014-02-01-Recently in the sister blog

17 0.067493774 716 andrew gelman stats-2011-05-17-Is the internet causing half the rapes in Norway? I wanna see the scatterplot.

18 0.0640264 1618 andrew gelman stats-2012-12-11-The consulting biz

19 0.057774957 1422 andrew gelman stats-2012-07-20-Likelihood thresholds and decisions

20 0.057418276 133 andrew gelman stats-2010-07-08-Gratuitous use of “Bayesian Statistics,” a branding issue?


similar blogs computed by lsi model

lsi for this blog:

topicId topicWeight

[(0, 0.098), (1, -0.026), (2, 0.053), (3, -0.01), (4, -0.003), (5, -0.018), (6, 0.025), (7, 0.009), (8, -0.014), (9, -0.022), (10, -0.03), (11, 0.005), (12, -0.002), (13, -0.017), (14, 0.004), (15, 0.034), (16, 0.027), (17, 0.006), (18, 0.005), (19, 0.016), (20, -0.004), (21, 0.041), (22, 0.006), (23, 0.004), (24, -0.001), (25, 0.009), (26, -0.021), (27, 0.011), (28, 0.016), (29, 0.019), (30, -0.01), (31, 0.014), (32, -0.019), (33, 0.003), (34, -0.004), (35, -0.007), (36, 0.031), (37, 0.013), (38, -0.006), (39, 0.008), (40, 0.005), (41, -0.016), (42, -0.04), (43, 0.005), (44, 0.024), (45, 0.001), (46, -0.022), (47, 0.021), (48, -0.001), (49, 0.049)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.95682645 549 andrew gelman stats-2011-02-01-“Roughly 90% of the increase in . . .” Hey, wait a minute!

Introduction: Matthew Yglesias links approvingly to the following statement by Michael Mandel: Homeland Security accounts for roughly 90% of the increase in federal regulatory employment over the past ten years. Roughly 90%, huh? That sounds pretty impressive. But wait a minute . . . what if total federal regulatory employment had increased a bit less. Then Homeland Security could’ve accounted for 105% of the increase, or 500% of the increase, or whatever. The point is the change in total employment is the sum of a bunch of pluses and minuses. It happens that, if you don’t count Homeland Security, the total hasn’t changed much–I’m assuming Mandel’s numbers are correct here–and that could be interesting. The “roughly 90%” figure is misleading because, when written as a percent of the total increase, it’s natural to quickly envision it as a percentage that is bounded by 100%. There is a total increase in regulatory employment that the individual agencies sum to, but some margins are p

2 0.76809686 1086 andrew gelman stats-2011-12-27-The most dangerous jobs in America

Introduction: Robin Hanson writes: On the criteria of potential to help people avoid death, this would seem to be among the most important news I’ve ever heard. [In his recent Ph.D. thesis , Ken Lee finds that] death rates depend on job details more than on race, gender, marriage status, rural vs. urban, education, and income  combined !  Now for the details. The US Department of Labor has described each of 807 occupations with over 200 detailed features on how jobs are done, skills required, etc.. Lee looked at seven domains of such features, each containing 16 to 57 features, and for each domain Lee did a factor analysis of those features to find the top 2-4 factors. This gave Lee a total of 22 domain factors. Lee also found four overall factors to describe his total set of 225 job and 9 demographic features. (These four factors explain 32%, 15%, 7%, and 4% of total variance.) Lee then tried to use these 26 job factors, along with his other standard predictors (age, race, gender, m

3 0.72130996 947 andrew gelman stats-2011-10-08-GiveWell sez: Cost-effectiveness of de-worming was overstated by a factor of 100 (!) due to a series of sloppy calculations

Introduction: Alexander at GiveWell writes : The Disease Control Priorities in Developing Countries (DCP2), a major report funded by the Gates Foundation . . . provides an estimate of $3.41 per disability-adjusted life-year (DALY) for the cost-effectiveness of soil-transmitted-helminth (STH) treatment, implying that STH treatment is one of the most cost-effective interventions for global health. In investigating this figure, we have corresponded, over a period of months, with six scholars who had been directly or indirectly involved in the production of the estimate. Eventually, we were able to obtain the spreadsheet that was used to generate the $3.41/DALY estimate. That spreadsheet contains five separate errors that, when corrected, shift the estimated cost effectiveness of deworming from $3.41 to $326.43. [I think they mean to say $300 -- ed.] We came to this conclusion a year after learning that the DCP2’s published cost-effectiveness estimate for schistosomiasis treatment – another kind of

4 0.71252054 1838 andrew gelman stats-2013-05-03-Setting aside the politics, the debate over the new health-care study reveals that we’re moving to a new high standard of statistical journalism

Introduction: Pointing to this news article by Megan McArdle discussing a recent study of Medicaid recipients, Jonathan Falk writes: Forget the interpretation for a moment, and the political spin, but haven’t we reached an interesting point when a journalist says things like: When you do an RCT with more than 12,000 people in it, and your defense of your hypothesis is that maybe the study just didn’t have enough power, what you’re actually saying is “the beneficial effects are probably pretty small”. and A good Bayesian—and aren’t most of us are supposed to be good Bayesians these days?—should be updating in light of this new information. Given this result, what is the likelihood that Obamacare will have a positive impact on the average health of Americans? Every one of us, for or against, should be revising that probability downwards. I’m not saying that you have to revise it to zero; I certainly haven’t. But however high it was yesterday, it should be somewhat lower today. This

5 0.71115035 629 andrew gelman stats-2011-03-26-Is it plausible that 1% of people pick a career based on their first name?

Introduction: In my discussion of dentists-named-Dennis study, I referred to my back-of-the-envelope calculation that the effect (if it indeed exists) corresponds to an approximate 1% aggregate chance that you’ll pick a profession based on your first name. Even if there are nearly twice as many dentist Dennises as would be expected from chance alone, the base rate is so low that a shift of 1% of all Dennises would be enough to do this. My point was that (a) even a small effect could show up when looking at low-frequency events such as the choice to pick a particular career or live in a particular city, and (b) any small effects will inherently be difficult to detect in any direct way. Uri Simonsohn (the author of the recent rebuttal of the original name-choice article by Brett Pelham et al.) wrote: In terms of the effect size. I [Simonsohn] think of it differently and see it as too big to be believable. I don’t find it plausible that I can double the odds that my daughter will marry an

6 0.71090931 2030 andrew gelman stats-2013-09-19-Is coffee a killer? I don’t think the effect is as high as was estimated from the highest number that came out of a noisy study

7 0.7104221 1397 andrew gelman stats-2012-06-27-Stand Your Ground laws and homicides

8 0.7078473 179 andrew gelman stats-2010-08-03-An Olympic size swimming pool full of lithium water

9 0.70707357 1187 andrew gelman stats-2012-02-27-“Apple confronts the law of large numbers” . . . huh?

10 0.70276749 504 andrew gelman stats-2011-01-05-For those of you in the U.K., also an amusing paradox involving the infamous hookah story

11 0.6995067 526 andrew gelman stats-2011-01-19-“If it saves the life of a single child…” and other nonsense

12 0.69827747 67 andrew gelman stats-2010-06-03-More on that Dartmouth health care study

13 0.69785047 1364 andrew gelman stats-2012-06-04-Massive confusion about a study that purports to show that exercise may increase heart risk

14 0.6956594 1522 andrew gelman stats-2012-10-05-High temperatures cause violent crime and implications for climate change, also some suggestions about how to better summarize these claims

15 0.69121957 584 andrew gelman stats-2011-02-22-“Are Wisconsin Public Employees Underpaid?”

16 0.68854004 944 andrew gelman stats-2011-10-05-How accurate is your gaydar?

17 0.68673176 2049 andrew gelman stats-2013-10-03-On house arrest for p-hacking

18 0.68416387 646 andrew gelman stats-2011-04-04-Graphical insights into the safety of cycling.

19 0.6831997 791 andrew gelman stats-2011-07-08-Censoring on one end, “outliers” on the other, what can we do with the middle?

20 0.67587334 284 andrew gelman stats-2010-09-18-Continuing efforts to justify false “death panels” claim


similar blogs computed by lda model

lda for this blog:

topicId topicWeight

[(2, 0.3), (9, 0.016), (15, 0.017), (16, 0.082), (19, 0.011), (21, 0.012), (22, 0.011), (24, 0.134), (53, 0.029), (55, 0.013), (99, 0.227)]

similar blogs list:

simIndex simValue blogId blogTitle

1 0.96631604 97 andrew gelman stats-2010-06-18-Economic Disparities and Life Satisfaction in European Regions

Introduction: Grazia Pittau, Roberto Zelli, and I came out with a paper investigating the role of economic variables in predicting regional disparities in reported life satisfaction of European Union citizens. We use multilevel modeling to explicitly account for the hierarchical nature of our data, respondents within regions and countries, and for understanding patterns of variation within and between regions. Here’s what we found: - Personal income matters more in poor regions than in rich regions, a pattern that still holds for regions within the same country. - Being unemployed is negatively associated with life satisfaction even after controlled for income variation. Living in high unemployment regions does not alleviate the unhappiness of being out of work. - After controlling for individual characteristics and modeling interactions, regional differences in life satisfaction still remain. Here’s a quick graph; there’s more in the article:

2 0.96499473 663 andrew gelman stats-2011-04-15-Happy tax day!

Introduction: Your taxes pay for the research funding that supports the work we do here, some of which appears on this blog and almost all of which is public, free, and open-source. So, to all of the taxpayers out there in the audience: thank you.

3 0.95131218 489 andrew gelman stats-2010-12-28-Brow inflation

Introduction: In an article headlined, “Hollywood moves away from middlebrow,” Brooks Barnes writes : As Hollywood plowed into 2010, there was plenty of clinging to the tried and true: humdrum remakes like “The Wolfman” and “The A-Team”; star vehicles like “Killers” with Ashton Kutcher and “The Tourist” with Angelina Jolie and Johnny Depp; and shoddy sequels like “Sex and the City 2.” All arrived at theaters with marketing thunder intended to fill multiplexes on opening weekend, no matter the quality of the film. . . . But the audience pushed back. One by one, these expensive yet middle-of-the-road pictures delivered disappointing results or flat-out flopped. Meanwhile, gambles on original concepts paid off. “Inception,” a complicated thriller about dream invaders, racked up more than $825 million in global ticket sales; “The Social Network” has so far delivered $192 million, a stellar result for a highbrow drama. . . . the message that the year sent about quality and originality is real enoug

same-blog 4 0.9467417 549 andrew gelman stats-2011-02-01-“Roughly 90% of the increase in . . .” Hey, wait a minute!

Introduction: Matthew Yglesias links approvingly to the following statement by Michael Mandel: Homeland Security accounts for roughly 90% of the increase in federal regulatory employment over the past ten years. Roughly 90%, huh? That sounds pretty impressive. But wait a minute . . . what if total federal regulatory employment had increased a bit less. Then Homeland Security could’ve accounted for 105% of the increase, or 500% of the increase, or whatever. The point is the change in total employment is the sum of a bunch of pluses and minuses. It happens that, if you don’t count Homeland Security, the total hasn’t changed much–I’m assuming Mandel’s numbers are correct here–and that could be interesting. The “roughly 90%” figure is misleading because, when written as a percent of the total increase, it’s natural to quickly envision it as a percentage that is bounded by 100%. There is a total increase in regulatory employment that the individual agencies sum to, but some margins are p

5 0.93923581 17 andrew gelman stats-2010-05-05-Taking philosophical arguments literally

Introduction: Aaron Swartz writes the following, as a lead-in to an argument in favor of vegetarianism: Imagine you were an early settler of what is now the United States. It seems likely you would have killed native Americans. After all, your parents killed them, your siblings killed them, your friends killed them, the leaders of the community killed them, the President killed them. Chances are, you would have killed them too . . . Or if you see nothing wrong with killing native Americans, take the example of slavery. Again, everyone had slaves and probably didn’t think too much about the morality of it. . . . Are these statements true, though? It’s hard for me to believe that most early settlers (from the context, it looks like Swartz is discussing the 1500s-1700s here) killed native Americans. That is, if N is the number of early settlers, and Y is the number of these settlers who killed at least one Indian, I suspect Y/N is much closer to 0 than to 1. Similarly, it’s not even cl

6 0.93445408 1017 andrew gelman stats-2011-11-18-Lack of complete overlap

7 0.93198979 1698 andrew gelman stats-2013-01-30-The spam just gets weirder and weirder

8 0.92216456 885 andrew gelman stats-2011-09-01-Needed: A Billionaire Candidate for President Who Shares the Views of a Washington Post Columnist

9 0.91539204 1189 andrew gelman stats-2012-02-28-Those darn physicists

10 0.91190326 44 andrew gelman stats-2010-05-20-Boris was right

11 0.90331781 1663 andrew gelman stats-2013-01-09-The effects of fiscal consolidation

12 0.89722836 1102 andrew gelman stats-2012-01-06-Bayesian Anova found useful in ecology

13 0.88901043 1508 andrew gelman stats-2012-09-23-Speaking frankly

14 0.88445109 1872 andrew gelman stats-2013-05-27-More spam!

15 0.86270916 1567 andrew gelman stats-2012-11-07-Election reports

16 0.86047459 1893 andrew gelman stats-2013-06-11-Folic acid and autism

17 0.8562535 1954 andrew gelman stats-2013-07-24-Too Good To Be True: The Scientific Mass Production of Spurious Statistical Significance

18 0.84418809 1260 andrew gelman stats-2012-04-11-Hunger Games survival analysis

19 0.83747327 2360 andrew gelman stats-2014-06-05-Identifying pathways for managing multiple disturbances to limit plant invasions

20 0.83484465 694 andrew gelman stats-2011-05-04-My talk at Hunter College on Thurs