andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1609 knowledge-graph by maker-knowledge-mining

1609 andrew gelman stats-2012-12-06-Stephen Kosslyn’s principles of graphics and one more: There’s no need to cram everything into a single plot


meta infos for this blog

Source: html

Introduction: Jerzy Wieczorek has an interesting review of the book Graph Design for the Eye and Mind by psychology researcher Stephen Kosslyn. I recommend you read all of Wieczorek’s review (and maybe Kosslyn’s book, but that I haven’t seen), but here I’ll just focus on one point. Here’s Wieczorek summarizing Kosslyn: p. 18-19: the horizontal axis should be for the variable with the “most important part of the data.” See Kosslyn’s Figure 1.6 and 1.7 below. Figure 1.6 clearly shows that one of the sex-by-income groups reacts to age differently than the other three groups do. Figure 1.7 uses sex as the x-axis variable, making it much harder to see this same effect in the data. As a statistician exploring the data, I might make several plots using different groupings… but for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. Those who know me well (or who have read the title of this post) will guess my reaction, whic


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 6 clearly shows that one of the sex-by-income groups reacts to age differently than the other three groups do. [sent-9, score-0.237]

2 As a statistician exploring the data, I might make several plots using different groupings… but for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. [sent-12, score-0.48]

3 Those who know me well (or who have read the title of this post) will guess my reaction, which is that Kosslyn is trying to cram too much into a single graph. [sent-13, score-0.238]

4 The circles and squares are hard to tell apart, the open and dark symbols are a bit confusing, and the lines are so thick that it’s hard to make out the symbols anyway. [sent-14, score-0.353]

5 As Kossyln himself notes, the purpose of a graph is to make comparisons, not to be used as a look-up table. [sent-16, score-0.157]

6 The structure of the (hypothetical) data being displayed is pretty simple: it’s a single continuous outcome as a function of three binary inputs. [sent-17, score-0.337]

7 In general I prefer to put continuous predictors on the x-axis and discrete predictors as separate lines, so that would rule out Kosslyn’s second graph (Figure 1. [sent-19, score-0.283]

8 Here’s another point not mentioned by Kosslyn (or, to be precise, not mentioned in Wieczorek’s review): What’s with those binary age and income variables? [sent-29, score-0.317]

9 In the above graph, it would be trivial to increase the number of age categories on the x-axis, and we could also increase the number of income categories by simply placing more graphs side by side. [sent-35, score-0.514]

10 We could even introduce another background variable (for example, ethnicity) by stacking these graphs in rows (as we did for our maps of voting by income, ethnicity, and state). [sent-36, score-0.207]

11 The above is not meant to disparage Kosslyn’s work, nor am I suggesting that my redrawn graphs are perfect. [sent-37, score-0.147]

12 Here I’m focusing on one single point, which is the virtue of small multiples (as Tufte puts it). [sent-38, score-0.287]

13 I just think that all of use get stuck in our ways of thinking, and I fear that Kosslyn has been stuck in the traditional idea that all the information should be conveyed in a single plot. [sent-41, score-0.317]

14 Hence I also object to Wieczorek’s statement, “for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. [sent-42, score-0.263]

15 ” Sometimes one plot will do, but other times you can make a single display with several plots to better make your point. [sent-43, score-0.725]

16 But as the example above illustrates, the small-multiples display can be cleaner than the one graph. [sent-48, score-0.313]

17 Minard was amazingly clever and managed to cram a huge amount of information into a single display, but I can’t agree that this is an effective way to communicate; the display doesn’t present the facts so that they’re clear or easily absorbed. [sent-50, score-0.67]

18 If you are in the mood, you may enjoy taking the time to study the display for the fun of solving a puzzle, pondering intricate details, or appreciating the graphic devices employed. [sent-51, score-0.231]

19 But if you want the facts and want them in a clear, easily understood way, this display is not the solution. [sent-52, score-0.285]

20 I just think Kosslyn needs to take the next step and recognize that, in his own field, you can get a cleaner picture with small multiples than by trying to fit all the information on a single plot. [sent-53, score-0.37]


similar blogs computed by tfidf model

tfidf for this blog:

wordName wordTfidf (topN-words)

[('kosslyn', 0.679), ('wieczorek', 0.283), ('display', 0.182), ('single', 0.151), ('figure', 0.119), ('lines', 0.117), ('graph', 0.107), ('graphs', 0.095), ('symbols', 0.093), ('income', 0.092), ('categories', 0.089), ('cram', 0.087), ('plots', 0.086), ('multiples', 0.085), ('several', 0.081), ('placing', 0.08), ('cleaner', 0.08), ('slopes', 0.078), ('continuous', 0.078), ('plot', 0.074), ('tufte', 0.073), ('communicating', 0.071), ('age', 0.069), ('shows', 0.067), ('ethnicity', 0.064), ('variable', 0.063), ('binary', 0.058), ('review', 0.057), ('facts', 0.057), ('stuck', 0.056), ('information', 0.054), ('jerzy', 0.052), ('discordant', 0.052), ('hash', 0.052), ('redrawn', 0.052), ('audience', 0.051), ('one', 0.051), ('make', 0.05), ('three', 0.05), ('mentioned', 0.049), ('predictors', 0.049), ('stacking', 0.049), ('stare', 0.049), ('groupings', 0.049), ('appreciating', 0.049), ('introspection', 0.049), ('amount', 0.047), ('granularity', 0.046), ('easily', 0.046), ('clear', 0.046)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.99999988 1609 andrew gelman stats-2012-12-06-Stephen Kosslyn’s principles of graphics and one more: There’s no need to cram everything into a single plot

Introduction: Jerzy Wieczorek has an interesting review of the book Graph Design for the Eye and Mind by psychology researcher Stephen Kosslyn. I recommend you read all of Wieczorek’s review (and maybe Kosslyn’s book, but that I haven’t seen), but here I’ll just focus on one point. Here’s Wieczorek summarizing Kosslyn: p. 18-19: the horizontal axis should be for the variable with the “most important part of the data.” See Kosslyn’s Figure 1.6 and 1.7 below. Figure 1.6 clearly shows that one of the sex-by-income groups reacts to age differently than the other three groups do. Figure 1.7 uses sex as the x-axis variable, making it much harder to see this same effect in the data. As a statistician exploring the data, I might make several plots using different groupings… but for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. Those who know me well (or who have read the title of this post) will guess my reaction, whic

2 0.17187504 878 andrew gelman stats-2011-08-29-Infovis, infographics, and data visualization: Where I’m coming from, and where I’d like to go

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

3 0.15801953 61 andrew gelman stats-2010-05-31-A data visualization manifesto

Introduction: Details matter (at least, they do for me), but we don’t yet have a systematic way of going back and forth between the structure of a graph, its details, and the underlying questions that motivate our visualizations. (Cleveland, Wilkinson, and others have written a bit on how to formalize these connections, and I’ve thought about it too, but we have a ways to go.) I was thinking about this difficulty after reading an article on graphics by some computer scientists that was well-written but to me lacked a feeling for the linkages between substantive/statistical goals and graphical details. I have problems with these issues too, and my point here is not to criticize but to move the discussion forward. When thinking about visualization, how important are the details? Aleks pointed me to this article by Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky, “A Tour through the Visualization Zoo: A survey of powerful visualization techniques, from the obvious to the obscure.” Th

4 0.15746242 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

5 0.14757383 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

6 0.13134564 1684 andrew gelman stats-2013-01-20-Ugly ugly ugly

7 0.12896642 1584 andrew gelman stats-2012-11-19-Tradeoffs in information graphics

8 0.12703967 252 andrew gelman stats-2010-09-02-R needs a good function to make line plots

9 0.12566778 1104 andrew gelman stats-2012-01-07-A compelling reason to go to London, Ontario??

10 0.11200602 847 andrew gelman stats-2011-08-10-Using a “pure infographic” to explore differences between information visualization and statistical graphics

11 0.11141028 488 andrew gelman stats-2010-12-27-Graph of the year

12 0.10874654 1439 andrew gelman stats-2012-08-01-A book with a bunch of simple graphs

13 0.1074753 1176 andrew gelman stats-2012-02-19-Standardized writing styles and standardized graphing styles

14 0.10604505 37 andrew gelman stats-2010-05-17-Is chartjunk really “more useful” than plain graphs? I don’t think so.

15 0.10333905 2319 andrew gelman stats-2014-05-05-Can we make better graphs of global temperature history?

16 0.10089644 2132 andrew gelman stats-2013-12-13-And now, here’s something that would make Ed Tufte spin in his . . . ummm, Tufte’s still around, actually, so let’s just say I don’t think he’d like it!

17 0.10011823 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year

18 0.099950671 324 andrew gelman stats-2010-10-07-Contest for developing an R package recommendation system

19 0.099830672 1606 andrew gelman stats-2012-12-05-The Grinch Comes Back

20 0.09898451 1896 andrew gelman stats-2013-06-13-Against the myth of the heroic visualization


similar blogs computed by lsi model

lsi for this blog:

topicId topicWeight

[(0, 0.186), (1, -0.03), (2, 0.011), (3, 0.05), (4, 0.143), (5, -0.151), (6, -0.066), (7, 0.049), (8, -0.01), (9, 0.027), (10, 0.011), (11, 0.003), (12, -0.027), (13, -0.008), (14, 0.053), (15, -0.009), (16, 0.02), (17, -0.006), (18, -0.007), (19, -0.002), (20, 0.015), (21, 0.032), (22, 0.005), (23, -0.009), (24, 0.012), (25, 0.002), (26, 0.059), (27, -0.012), (28, -0.012), (29, 0.009), (30, 0.021), (31, -0.004), (32, -0.047), (33, -0.003), (34, 0.014), (35, -0.031), (36, 0.003), (37, -0.022), (38, -0.026), (39, -0.012), (40, 0.021), (41, -0.01), (42, 0.024), (43, 0.03), (44, -0.028), (45, -0.03), (46, -0.019), (47, 0.023), (48, 0.011), (49, 0.034)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.96837109 1609 andrew gelman stats-2012-12-06-Stephen Kosslyn’s principles of graphics and one more: There’s no need to cram everything into a single plot

Introduction: Jerzy Wieczorek has an interesting review of the book Graph Design for the Eye and Mind by psychology researcher Stephen Kosslyn. I recommend you read all of Wieczorek’s review (and maybe Kosslyn’s book, but that I haven’t seen), but here I’ll just focus on one point. Here’s Wieczorek summarizing Kosslyn: p. 18-19: the horizontal axis should be for the variable with the “most important part of the data.” See Kosslyn’s Figure 1.6 and 1.7 below. Figure 1.6 clearly shows that one of the sex-by-income groups reacts to age differently than the other three groups do. Figure 1.7 uses sex as the x-axis variable, making it much harder to see this same effect in the data. As a statistician exploring the data, I might make several plots using different groupings… but for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. Those who know me well (or who have read the title of this post) will guess my reaction, whic

2 0.92455465 1439 andrew gelman stats-2012-08-01-A book with a bunch of simple graphs

Introduction: Howard Friedman sent me a new book, The Measure of a Nation, subtitled How to Regain America’s Competitive Edge and Boost Our Global Standing. Without commenting on the substance of Friedman’s recommendations, I’d like to endorse his strategy of presentation, which is to display graph after graph after graph showing the same message over and over again, which is that the U.S. is outperformed by various other countries (mostly in Europe) on a variety of measures. These aren’t graphs I would ever make—they are scatterplots in which the x-axis conveys no information. But they have the advantage of repetition: once you figure out how to read one of the graphs, you can read the others easily. Here’s an example which I found from a quick Google: I can’t actually figure out what is happening on the x-axis, nor do I understand the “star, middle child, dog” thing. But I like the use of graphics. Lots more fun than bullet points. Seriously. P.S. Just to be clear: I am not trying

3 0.91817838 1684 andrew gelman stats-2013-01-20-Ugly ugly ugly

Introduction: Denis Cote sends the following , under the heading, “Some bad graphs for your enjoyment”: To start with, they don’t know how to spell “color.” Seriously, though, the graph is a mess. The circular display implies a circular or periodic structure that isn’t actually in the data, the cramped display requires the use of an otherwise-unnecessary color code that makes it difficult to find or make sense of the information, the alphabetical ordering (without even supplying state names, only abbreviations) makes it further difficult to find any patterns. It would be so much better, and even easier, to just display a set of small maps shading states on whether they have different laws. But that’s part of the problem—the clearer graph would also be easier to make! To get a distinctive graph, there needs to be some degree of difficulty. The designers continue with these monstrosities: Here they decide to display only 5 states at a time so that it’s really hard to see any big pi

4 0.88376266 61 andrew gelman stats-2010-05-31-A data visualization manifesto

Introduction: Details matter (at least, they do for me), but we don’t yet have a systematic way of going back and forth between the structure of a graph, its details, and the underlying questions that motivate our visualizations. (Cleveland, Wilkinson, and others have written a bit on how to formalize these connections, and I’ve thought about it too, but we have a ways to go.) I was thinking about this difficulty after reading an article on graphics by some computer scientists that was well-written but to me lacked a feeling for the linkages between substantive/statistical goals and graphical details. I have problems with these issues too, and my point here is not to criticize but to move the discussion forward. When thinking about visualization, how important are the details? Aleks pointed me to this article by Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky, “A Tour through the Visualization Zoo: A survey of powerful visualization techniques, from the obvious to the obscure.” Th

5 0.87946153 37 andrew gelman stats-2010-05-17-Is chartjunk really “more useful” than plain graphs? I don’t think so.

Introduction: Helen DeWitt links to this blog that reports on a study by Scott Bateman, Carl Gutwin, David McDine, Regan Mandryk, Aaron Genest, and Christopher Brooks that claims the following: Guidelines for designing information charts often state that the presentation should reduce ‘chart junk’–visual embellishments that are not essential to understanding the data. . . . we conducted an experiment that compared embellished charts with plain ones, and measured both interpretation accuracy and long-term recall. We found that people’s accuracy in describing the embellished charts was no worse than for plain charts, and that their recall after a two-to-three-week gap was significantly better. As the above-linked blogger puts it, “chartjunk is more useful than plain graphs. . . . Tufte is not going to like this.” I can’t speak for Ed Tufte, but I’m not gonna take this claim about chartjunk lying down. I have two points to make which I hope can stop the above-linked study from being sla

6 0.86983907 2266 andrew gelman stats-2014-03-25-A statistical graphics course and statistical graphics advice

7 0.86849934 672 andrew gelman stats-2011-04-20-The R code for those time-use graphs

8 0.86549294 1606 andrew gelman stats-2012-12-05-The Grinch Comes Back

9 0.85675412 488 andrew gelman stats-2010-12-27-Graph of the year

10 0.85401052 2154 andrew gelman stats-2013-12-30-Bill Gates’s favorite graph of the year

11 0.85132372 829 andrew gelman stats-2011-07-29-Infovis vs. statgraphics: A clear example of their different goals

12 0.85027981 671 andrew gelman stats-2011-04-20-One more time-use graph

13 0.84759629 1894 andrew gelman stats-2013-06-12-How to best graph the Beveridge curve, relating the vacancy rate in jobs to the unemployment rate?

14 0.84745455 878 andrew gelman stats-2011-08-29-Infovis, infographics, and data visualization: Where I’m coming from, and where I’d like to go

15 0.84742874 2246 andrew gelman stats-2014-03-13-An Economist’s Guide to Visualizing Data

16 0.84578365 502 andrew gelman stats-2011-01-04-Cash in, cash out graph

17 0.84034264 1059 andrew gelman stats-2011-12-14-Looking at many comparisons may increase the risk of finding something statistically significant by epidemiologists, a population with relatively low multilevel modeling consumption

18 0.83226174 1896 andrew gelman stats-2013-06-13-Against the myth of the heroic visualization

19 0.83135033 1011 andrew gelman stats-2011-11-15-World record running times vs. distance

20 0.8313154 296 andrew gelman stats-2010-09-26-A simple semigraphic display


similar blogs computed by lda model

lda for this blog:

topicId topicWeight

[(5, 0.021), (13, 0.013), (16, 0.073), (21, 0.02), (24, 0.182), (31, 0.011), (55, 0.013), (63, 0.024), (76, 0.214), (77, 0.022), (86, 0.026), (99, 0.231)]

similar blogs list:

simIndex simValue blogId blogTitle

1 0.93375194 988 andrew gelman stats-2011-11-02-Roads, traffic, and the importance in decision analysis of carefully examining your goals

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

2 0.9292596 1551 andrew gelman stats-2012-10-28-A convenience sample and selected treatments

Introduction: Charlie Saunders writes: A study has recently been published in the New England Journal of Medicine (NEJM) which uses survival analysis to examine long-acting reversible contraception (e.g. intrauterine devices [IUDs]) vs. short-term commonly prescribed methods of contraception (e.g. oral contraceptive pills) on unintended pregnancies. The authors use a convenience sample of over 7,000 women. I am not well versed-enough in sampling theory to determine the appropriateness of this but it would seem that the use of a non-probability sampling would be a significant drawback. If you could give me your opinion on this, I would appreciate it. The NEJM is one of the top medical journals in the country. Could this type of sampling method coupled with this method of analysis be published in a journal like JASA? My reply: There are two concerns, first that it is a convenience sample and thus not representative of the population, and second that the treatments are chosen rather tha

3 0.9189828 300 andrew gelman stats-2010-09-28-A calibrated Cook gives Dems the edge in Nov, sez Sandy

Introduction: Sandy Gordon sends along this fun little paper forecasting the 2010 midterm election using expert predictions (the Cook and Rothenberg Political Reports). Gordon’s gimmick is that he uses past performance to calibrate the reports’ judgments based on “solid,” “likely,” “leaning,” and “toss-up” categories, and then he uses the calibrated versions of the current predictions to make his forecast. As I wrote a few weeks ago in response to Nate’s forecasts, I think the right way to go, if you really want to forecast the election outcome, is to use national information to predict the national swing and then do regional, state, and district-level adjustments using whatever local information is available. I don’t see the point of using only the expert forecasts and no other data. Still, Gordon is bringing new information (his calibrations) to the table, so I wanted to share it with you. Ultimately I like the throw-in-everything approach that Nate uses (although I think Nate’s descr

same-blog 4 0.91571784 1609 andrew gelman stats-2012-12-06-Stephen Kosslyn’s principles of graphics and one more: There’s no need to cram everything into a single plot

Introduction: Jerzy Wieczorek has an interesting review of the book Graph Design for the Eye and Mind by psychology researcher Stephen Kosslyn. I recommend you read all of Wieczorek’s review (and maybe Kosslyn’s book, but that I haven’t seen), but here I’ll just focus on one point. Here’s Wieczorek summarizing Kosslyn: p. 18-19: the horizontal axis should be for the variable with the “most important part of the data.” See Kosslyn’s Figure 1.6 and 1.7 below. Figure 1.6 clearly shows that one of the sex-by-income groups reacts to age differently than the other three groups do. Figure 1.7 uses sex as the x-axis variable, making it much harder to see this same effect in the data. As a statistician exploring the data, I might make several plots using different groupings… but for communicating my results to an audience, I would choose the one plot that shows the findings most clearly. Those who know me well (or who have read the title of this post) will guess my reaction, whic

5 0.90947485 1084 andrew gelman stats-2011-12-26-Tweeting the Hits?

Introduction: Someone sent me an email saying that he liked my little essay, “Descriptive statistics aren’t just for losers.” I had no idea what he was talking about, but it sounded like the kind of thing I’d say, so I searched the blog and found this post , which indeed I really like! I thanked my correspondent for reminding me of this little article I’d forgotten, and he told me he just learned of it via someone’s tweet. This made me think: Maybe I should have a twitter feed of nothing but old blog entries. I could just go back to 2004 and then go gradually forward, tweeting the items that I judge to remain of interest. Does this make sense? Or is there a better way to do this? ALternatively, I could do it as a separate blog, but that seems a bit . . . recursive.

6 0.90094018 1351 andrew gelman stats-2012-05-29-A Ph.D. thesis is not really a marathon

7 0.88104415 337 andrew gelman stats-2010-10-12-Election symposium at Columbia Journalism School

8 0.87762475 1850 andrew gelman stats-2013-05-10-The recursion of pop-econ

9 0.87563127 1818 andrew gelman stats-2013-04-22-Goal: Rules for Turing chess

10 0.8676883 2246 andrew gelman stats-2014-03-13-An Economist’s Guide to Visualizing Data

11 0.86672592 283 andrew gelman stats-2010-09-17-Vote Buying: Evidence from a List Experiment in Lebanon

12 0.85702133 1835 andrew gelman stats-2013-05-02-7 ways to separate errors from statistics

13 0.85517484 257 andrew gelman stats-2010-09-04-Question about standard range for social science correlations

14 0.84732604 32 andrew gelman stats-2010-05-14-Causal inference in economics

15 0.84691107 608 andrew gelman stats-2011-03-12-Single or multiple imputation?

16 0.84342146 351 andrew gelman stats-2010-10-18-“I was finding the test so irritating and boring that I just started to click through as fast as I could”

17 0.84165132 51 andrew gelman stats-2010-05-26-If statistics is so significantly great, why don’t statisticians use statistics?

18 0.83949518 368 andrew gelman stats-2010-10-25-Is instrumental variables analysis particularly susceptible to Type M errors?

19 0.83170068 2013 andrew gelman stats-2013-09-08-What we need here is some peer review for statistical graphics

20 0.82881099 1105 andrew gelman stats-2012-01-08-Econ debate about prices at a fancy restaurant