andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1668 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: It’s in midtown at 7pm (on Mon 14 Jan 2013). Last time I talked for this group, I spoke on Infovis vs. Statistical Graphics . This time I plan to just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there will be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
sentIndex sentText sentNum sentScore
1 Last time I talked for this group, I spoke on Infovis vs. [sent-2, score-0.385]
2 This time I plan to just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. [sent-4, score-2.261]
3 For this talk there will be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. [sent-5, score-1.303]
4 I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. [sent-6, score-1.228]
wordName wordTfidf (topN-words)
[('tried', 0.322), ('choices', 0.258), ('midtown', 0.226), ('involved', 0.218), ('comparisons', 0.212), ('thru', 0.206), ('jan', 0.19), ('graphs', 0.185), ('zillion', 0.179), ('yair', 0.167), ('mon', 0.167), ('talk', 0.167), ('occasion', 0.166), ('infovis', 0.166), ('spoke', 0.161), ('theme', 0.16), ('options', 0.149), ('exploratory', 0.144), ('talked', 0.142), ('graphical', 0.133), ('ve', 0.127), ('voting', 0.12), ('plan', 0.12), ('decisions', 0.119), ('graphics', 0.115), ('testing', 0.114), ('except', 0.112), ('fun', 0.109), ('worked', 0.102), ('hypothesis', 0.101), ('usual', 0.101), ('bunch', 0.099), ('open', 0.098), ('sorts', 0.098), ('discussed', 0.093), ('single', 0.092), ('group', 0.091), ('time', 0.082), ('writing', 0.075), ('published', 0.072), ('last', 0.072), ('never', 0.068), ('didn', 0.067), ('give', 0.066), ('perhaps', 0.063), ('models', 0.063), ('discussion', 0.061), ('sense', 0.06), ('go', 0.057), ('years', 0.054)]
simIndex simValue blogId blogTitle
same-blog 1 0.99999988 1668 andrew gelman stats-2013-01-11-My talk at the NY data visualization meetup this Monday!
Introduction: It’s in midtown at 7pm (on Mon 14 Jan 2013). Last time I talked for this group, I spoke on Infovis vs. Statistical Graphics . This time I plan to just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there will be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
2 0.84297049 1450 andrew gelman stats-2012-08-08-My upcoming talk for the data visualization meetup
Introduction: Somebody asked me to speak sometime at a data visualization meetup. I think I spoke there a year or two ago but I could do it again. Last time I spoke on Infovis vs Statistical Graphics , this time I could just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there would be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
3 0.19597328 855 andrew gelman stats-2011-08-16-Infovis and statgraphics update update
Introduction: To continue our discussion from last week , consider three positions regarding the display of information: (a) The traditional tabular approach. This is how most statisticians, econometricians, political scientists, sociologists, etc., seem to operate. They understand the appeal of a pretty graph, and they’re willing to plot some data as part of an exploratory data analysis, but they see their serious research as leading to numerical estimates, p-values, tables of numbers. These people might use a graph to illustrate their points but they don’t see them as necessary in their research. (b) Statistical graphics as performed by Howard Wainer, Bill Cleveland, Dianne Cook, etc. They–we–see graphics as central to the process of statistical modeling and data analysis and are interested in graphs (static and dynamic) that display every data point as transparently as possible. (c) Information visualization or infographics, as performed by graphics designers and statisticians who are
4 0.17839101 2266 andrew gelman stats-2014-03-25-A statistical graphics course and statistical graphics advice
Introduction: Dean Eckles writes: Some of my coworkers at Facebook and I have worked with Udacity to create an online course on exploratory data analysis, including using data visualizations in R as part of EDA. The course has now launched at https://www.udacity.com/course/ud651 so anyone can take it for free. And Kaiser Fung has reviewed it . So definitely feel free to promote it! Criticism is also welcome (we are still fine-tuning things and adding more notes throughout). I wrote some more comments about the course here , including highlighting the interviews with my great coworkers. I didn’t have a chance to look at the course so instead I responded with some generic comments about eda and visualization (in no particular order): - Think of a graph as a comparison. All graphs are comparison (indeed, all statistical analyses are comparisons). If you already have the graph in mind, think of what comparisons it’s enabling. Or if you haven’t settled on the graph yet, think of what
Introduction: I continue to struggle to convey my thoughts on statistical graphics so I’ll try another approach, this time giving my own story. For newcomers to this discussion: the background is that Antony Unwin and I wrote an article on the different goals embodied in information visualization and statistical graphics, but I have difficulty communicating on this point with the infovis people. Maybe if I tell my own story, and then they tell their stories, this will point a way forward to a more constructive discussion. So here goes. I majored in physics in college and I worked in a couple of research labs during the summer. Physicists graph everything. I did most of my plotting on graph paper–this continued through my second year of grad school–and became expert at putting points at 1/5, 2/5, 3/5, and 4/5 between the x and y grid lines. In grad school in statistics, I continued my physics habits and graphed everything I could. I did notice, though, that the faculty and the other
6 0.16314715 548 andrew gelman stats-2011-02-01-What goes around . . .
7 0.15844396 2279 andrew gelman stats-2014-04-02-Am I too negative?
8 0.14871953 1764 andrew gelman stats-2013-03-15-How do I make my graphs?
9 0.14055704 1594 andrew gelman stats-2012-11-28-My talk on statistical graphics at Mit this Thurs aft
10 0.13933727 319 andrew gelman stats-2010-10-04-“Who owns Congress”
11 0.12766458 1584 andrew gelman stats-2012-11-19-Tradeoffs in information graphics
13 0.12261014 2275 andrew gelman stats-2014-03-31-Just gave a talk
14 0.12235741 1066 andrew gelman stats-2011-12-17-Ripley on model selection, and some links on exploratory model analysis
15 0.12173147 816 andrew gelman stats-2011-07-22-“Information visualization” vs. “Statistical graphics”
16 0.12127844 1848 andrew gelman stats-2013-05-09-A tale of two discussion papers
17 0.11730434 1806 andrew gelman stats-2013-04-16-My talk in Chicago this Thurs 6:30pm
18 0.11520679 1824 andrew gelman stats-2013-04-25-Fascinating graphs from facebook data
19 0.11228334 423 andrew gelman stats-2010-11-20-How to schedule projects in an introductory statistics course?
20 0.10660125 697 andrew gelman stats-2011-05-05-A statistician rereads Bill James
topicId topicWeight
[(0, 0.163), (1, -0.028), (2, -0.087), (3, 0.054), (4, 0.1), (5, -0.128), (6, -0.134), (7, 0.047), (8, -0.029), (9, -0.057), (10, 0.027), (11, 0.106), (12, 0.03), (13, -0.005), (14, 0.038), (15, -0.128), (16, -0.064), (17, -0.113), (18, 0.061), (19, 0.071), (20, -0.037), (21, -0.066), (22, 0.077), (23, 0.019), (24, -0.14), (25, -0.051), (26, -0.08), (27, -0.102), (28, 0.049), (29, -0.051), (30, -0.04), (31, 0.017), (32, 0.078), (33, 0.035), (34, -0.014), (35, -0.055), (36, 0.121), (37, 0.079), (38, 0.026), (39, 0.045), (40, -0.042), (41, 0.069), (42, -0.055), (43, -0.063), (44, -0.038), (45, -0.163), (46, -0.026), (47, 0.001), (48, 0.008), (49, -0.064)]
simIndex simValue blogId blogTitle
same-blog 1 0.98300654 1668 andrew gelman stats-2013-01-11-My talk at the NY data visualization meetup this Monday!
Introduction: It’s in midtown at 7pm (on Mon 14 Jan 2013). Last time I talked for this group, I spoke on Infovis vs. Statistical Graphics . This time I plan to just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there will be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
2 0.95930147 1450 andrew gelman stats-2012-08-08-My upcoming talk for the data visualization meetup
Introduction: Somebody asked me to speak sometime at a data visualization meetup. I think I spoke there a year or two ago but I could do it again. Last time I spoke on Infovis vs Statistical Graphics , this time I could just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there would be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
3 0.70704561 546 andrew gelman stats-2011-01-31-Infovis vs. statistical graphics: My talk tomorrow (Tues) 1pm at Columbia
Introduction: Infovis vs. statistical graphics . Tues 1 Feb 2011 1pm, Avery Hall room 114. It’s for the Lectures in Planning Series at the School of Architecture, Planning, and Preservation. Background on the talk (joint with Antony Unwin) is here . And here are more of my thoughts on statistical graphics.
4 0.65277457 548 andrew gelman stats-2011-02-01-What goes around . . .
Introduction: A few weeks ago I delivered a 10-minute talk on statistical graphics that went so well, it was the best-received talk I’ve ever given. The crowd was raucous. Then some poor sap had to go on after me. He started by saying that my talk was a hard act to follow. And, indeed, the audience politely listened but did not really get involved in his presentation. Boy did I feel smug. More recently I gave a talk on Stan, at an entirely different venue. And this time the story was the exact opposite. Jim Demmel spoke first and gave a wonderful talk on optimization for linear algebra (it was an applied math conference). Then I followed, and I never really grabbed the crowd. My talk was not a disaster but it didn’t really work. This was particularly frustrating because I’m really excited about Stan and this was a group of researchers I wouldn’t usually have a chance to reach. It was the plenary session at the conference. Anyway, now I know how that guy felt from last month. My talk
5 0.64850354 2275 andrew gelman stats-2014-03-31-Just gave a talk
Introduction: I just gave a talk in Milan. Actually I was sitting at my desk, it was a g+ hangout which was a bit more convenient for me. The audience was a bunch of astronomers so I figured they could handle a satellite link. . . . Anyway, the talk didn’t go so well. Two reasons: first, it’s just hard to get the connection with the audience without being able to see their faces. Next time I think I’ll try to get several people in the audience to open up their laptops and connect to the hangout, so that I can see a mosaic of faces instead of just a single image from the front of the room. The second problem with the talk was the topic. I asked the people who invited me to choose a topic, and they picked Can we use Bayesian methods to resolve the current crisis of statistically-significant research findings that don’t hold up? But I don’t think this was right for this audience. I think that it would’ve been better to give them the Stan talk or the little data talk or the statistic
6 0.63586175 407 andrew gelman stats-2010-11-11-Data Visualization vs. Statistical Graphics
7 0.62536764 1598 andrew gelman stats-2012-11-30-A graphics talk with no visuals!
8 0.61680841 438 andrew gelman stats-2010-11-30-I just skyped in from Kentucky, and boy are my arms tired
9 0.61285281 855 andrew gelman stats-2011-08-16-Infovis and statgraphics update update
11 0.5946241 1824 andrew gelman stats-2013-04-25-Fascinating graphs from facebook data
12 0.5899182 1594 andrew gelman stats-2012-11-28-My talk on statistical graphics at Mit this Thurs aft
13 0.58945227 794 andrew gelman stats-2011-07-09-The quest for the holy graph
14 0.58157557 492 andrew gelman stats-2010-12-30-That puzzle-solving feeling
15 0.58104199 319 andrew gelman stats-2010-10-04-“Who owns Congress”
16 0.57859433 1584 andrew gelman stats-2012-11-19-Tradeoffs in information graphics
17 0.57457852 1806 andrew gelman stats-2013-04-16-My talk in Chicago this Thurs 6:30pm
18 0.56339759 1066 andrew gelman stats-2011-12-17-Ripley on model selection, and some links on exploratory model analysis
19 0.55750883 1275 andrew gelman stats-2012-04-22-Please stop me before I barf again
20 0.55698895 2266 andrew gelman stats-2014-03-25-A statistical graphics course and statistical graphics advice
topicId topicWeight
[(0, 0.039), (16, 0.038), (24, 0.175), (47, 0.254), (51, 0.04), (85, 0.023), (99, 0.312)]
simIndex simValue blogId blogTitle
1 0.9590404 275 andrew gelman stats-2010-09-14-Data visualization at the American Evaluation Association
Introduction: Stephanie Evergreen writes: Media, web design, and marketing have all created an environment where stakeholders – clients, program participants, funders – all expect high quality graphics and reporting that effectively conveys the valuable insights from evaluation work. Some in statistics and mathematics have used data visualization strategies to support more useful reporting of complex ideas. Global growing interest in improving communications has begun to take root in the evaluation field as well. But as anyone who has sat through a day’s worth of a conference or had to endure a dissertation-worthy evaluation report knows, evaluators still have a long way to go. To support the development of researchers and evaluators, some members of the American Evaluation Association are proposing a new TIG (Topical Interest Group) on Data Visualization and Reporting. If you are a member of AEA (or want to be) and you are interested in joining this TIG, contact Stephanie Evergreen.
2 0.92808402 1055 andrew gelman stats-2011-12-13-Data sharing update
Introduction: Fred Oswald reports that Sian Beilock sent him sufficient amounts of raw data from her research study so allow him to answer his questions about the large effects that were observed. This sort of collegiality is central to the collective scientific enterprise. The bad news is that IRB’s are still getting in the way. Beilock was very helpful but she had to work within the constraints of her IRB, which apparently advised her not to share data—even if de-identified—without getting lots more permissions. Oswald writes: It is a little concerning that the IRB bars the sharing of de-identified data, particularly in light of the specific guidelines of the journal Science, which appears to say that when you submit a study to the journal for publication, you are allowing for the sharing of de-identified data — unless you expressly say otherwise at the point that you submit the paper for consideration. Again, I don’t blame Beilock and Ramirez—they appear to have been as helpful as
same-blog 3 0.91999435 1668 andrew gelman stats-2013-01-11-My talk at the NY data visualization meetup this Monday!
Introduction: It’s in midtown at 7pm (on Mon 14 Jan 2013). Last time I talked for this group, I spoke on Infovis vs. Statistical Graphics . This time I plan to just go thru the choices involved in a few zillion graphs I’ve published over the years, to give a sense of the options and choices involved in graphical communication. For this talk there will be no single theme (except, perhaps, my usual “Graphs as comparisons,” “All of statistics as comparisons,” and “Exploratory data analysis as hypothesis testing”), just a bunch of open discussion about what I tried, why I tried it, what worked and what didn’t work, etc. I’ve discussed these sorts of decisions on occasion (and am now writing a paper with Yair about some of this for our voting models), but I’ve never tried to make a talk out of it before. Could be fun.
Introduction: Remember How to Lie With Statistics? It turns out that the author worked for the cigarette companies. John Mashey points to this, from Robert Proctor’s book, “Golden Holocaust: Origins of the Cigarette Catastrophe and the Case for Abolition”: Darrell Huff, author of the wildly popular (and aptly named) How to Lie With Statistics, was paid to testify before Congress in the 1950s and then again in the 1960s, with the assigned task of ridiculing any notion of a cigarette-disease link. On March 22, 1965, Huff testified at hearings on cigarette labeling and advertising, accusing the recent Surgeon General’s report of myriad failures and “fallacies.” Huff peppered his attack with with amusing asides and anecdotes, lampooning spurious correlations like that between the size of Dutch families and the number of storks nesting on rooftops–which proves not that storks bring babies but rather that people with large families tend to have larger houses (which therefore attract more storks).
5 0.91442299 95 andrew gelman stats-2010-06-17-“Rewarding Strivers: Helping Low-Income Students Succeed in College”
Introduction: Several years ago, I heard about a project at the Educational Testing Service to identify “strivers”: students from disadvantaged backgrounds who did unexpectedly well on the SAT (the college admissions exam formerly known as the “Scholastic Aptitude Test” but apparently now just “the SAT,” in the same way that Exxon is just “Exxon” and that Harry Truman’s middle name is just “S”), at least 200 points above a predicted score based on demographic and neighborhood information. My ETS colleague and I agreed that this was a silly idea: From a statistical point of view, if student A is expected ahead of time to do better than student B, and then they get identical test scores, then you’d expect student A (the non-”striver”) to do better than student B (the “striver”) later on. Just basic statistics: if a student does much better than expected, then probably some of that improvement is noise. The idea of identifying these “strivers” seemed misguided and not the best use of the SAT.
6 0.90681028 1050 andrew gelman stats-2011-12-10-Presenting at the econ seminar
7 0.90365392 2275 andrew gelman stats-2014-03-31-Just gave a talk
8 0.90227199 1261 andrew gelman stats-2012-04-12-The Naval Research Lab
9 0.89994651 1897 andrew gelman stats-2013-06-13-When’s that next gamma-ray blast gonna come, already?
11 0.88849604 1143 andrew gelman stats-2012-01-29-G+ > Skype
12 0.87548774 1486 andrew gelman stats-2012-09-07-Prior distributions for regression coefficients
13 0.87223947 2290 andrew gelman stats-2014-04-14-On deck this week
14 0.87195086 716 andrew gelman stats-2011-05-17-Is the internet causing half the rapes in Norway? I wanna see the scatterplot.
15 0.86740476 548 andrew gelman stats-2011-02-01-What goes around . . .
16 0.86569566 1450 andrew gelman stats-2012-08-08-My upcoming talk for the data visualization meetup
17 0.86364174 1730 andrew gelman stats-2013-02-20-Unz on Unz
18 0.86088967 1349 andrew gelman stats-2012-05-28-Question 18 of my final exam for Design and Analysis of Sample Surveys
19 0.85906458 2068 andrew gelman stats-2013-10-18-G+ hangout for Bayesian Data Analysis course now! (actually, in 5 minutes)
20 0.8577649 1218 andrew gelman stats-2012-03-18-Check your missing-data imputations using cross-validation