andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1747 knowledge-graph by maker-knowledge-mining
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Introduction: Ruth Rosenholtz of the department of Brain and Cognitive Science at MIT writes: We mostly do computational modeling of human vision. We try to do on the one hand the sort of basic science that fits in the human vision community, while on the other hand developing predictive models which might actually lend insight into design. Your talk resonated with me in part because of this paper [Do Predictions of Visual Perception Aid Design?, by Ruth Rosenholtz, Amal Dorai, and Rosalind Freeman]. We went into our study thinking that people would like to have a quantitative tool to help analyze designs. But what we concluded, somewhat anecdotally, was that its main use seemed to be as a conversation-starter, and a means of communicating ideas about the design. And the reason it seemed to work is that our visualizations were the right level of a “puzzle” — challenging enough to be a bit fun to work out. On another topic, check out the infographic from last weekend’s NYTimes ma
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1 Ruth Rosenholtz of the department of Brain and Cognitive Science at MIT writes: We mostly do computational modeling of human vision. [sent-1, score-0.198]
2 We try to do on the one hand the sort of basic science that fits in the human vision community, while on the other hand developing predictive models which might actually lend insight into design. [sent-2, score-0.821]
3 Your talk resonated with me in part because of this paper [Do Predictions of Visual Perception Aid Design? [sent-3, score-0.151]
4 We went into our study thinking that people would like to have a quantitative tool to help analyze designs. [sent-5, score-0.234]
5 But what we concluded, somewhat anecdotally, was that its main use seemed to be as a conversation-starter, and a means of communicating ideas about the design. [sent-6, score-0.222]
6 And the reason it seemed to work is that our visualizations were the right level of a “puzzle” — challenging enough to be a bit fun to work out. [sent-7, score-0.321]
7 On another topic, check out the infographic from last weekend’s NYTimes magazine. [sent-8, score-0.108]
8 Where are the actors in “Nashville” actually from? [sent-9, score-0.229]
9 One might think this should be shown geographically, though perhaps not in a 2″x2″ space. [sent-10, score-0.077]
10 So they made a table (two columns: actor, where they are from), then scrambled the first column. [sent-13, score-0.293]
11 Then connected names to locations with colored line segments. [sent-14, score-0.397]
12 I said to my husband, “why would anyone do this? [sent-15, score-0.086]
13 ” He said, “I guess it makes you have to spend time to puzzle it out. [sent-16, score-0.197]
14 ” Recall our recent discussion [link fixed] of the confusing and visually-appealing Christmas tree graph. [sent-17, score-0.194]
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Introduction: Ruth Rosenholtz of the department of Brain and Cognitive Science at MIT writes: We mostly do computational modeling of human vision. We try to do on the one hand the sort of basic science that fits in the human vision community, while on the other hand developing predictive models which might actually lend insight into design. Your talk resonated with me in part because of this paper [Do Predictions of Visual Perception Aid Design?, by Ruth Rosenholtz, Amal Dorai, and Rosalind Freeman]. We went into our study thinking that people would like to have a quantitative tool to help analyze designs. But what we concluded, somewhat anecdotally, was that its main use seemed to be as a conversation-starter, and a means of communicating ideas about the design. And the reason it seemed to work is that our visualizations were the right level of a “puzzle” — challenging enough to be a bit fun to work out. On another topic, check out the infographic from last weekend’s NYTimes ma
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
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