Raise your hand if you knew that Ahmad Chalabi was a UofC alum? Jesus christ, not only did the end of the world begin there but the continued fucking over is also sucking on its teat.
Thursday, January 28, 2010
Randy Winn?
It's nice to see that the Yankees have finally just become a shitty Fantasy baseball team. Randy Winn? Really?
Friday, January 22, 2010
Massholes?
Parson me for posting a half-assed culture column on Slate, but I'd be interested to know what the Paul Revere in the HPD crowd thinks about massholes. Discuss.
put it on for my city
god DAMN oil can is looking good there -- note his full OCB embroidered on the warmup top and his SHADES. oil can boyd invented skinny-pants rap!
i'm still keeping matt kemp
Thursday, January 21, 2010
Wednesday, January 20, 2010
Scott Brown is bathroom material
The only good thing about Scott Brown's victory?
Scott Brown and Burt Reynolds both appeared nude in Cosmo.
Burt Reynolds appeared in Cannonball Run II, with Tony Danza.
Tony Danza appeared in Going Ape! with Manis (as the Main Monkey).
Manis (as Clyde) appeared in Every Which Way But Loose, with Clint Eastwood.
Clint Eastwood appeared in Pale Rider, with Chris Penn.
And Chris Penn appeared in Footloose, with Kevin Bacon.
Scott Brown and Burt Reynolds both appeared nude in Cosmo.
Burt Reynolds appeared in Cannonball Run II, with Tony Danza.
Tony Danza appeared in Going Ape! with Manis (as the Main Monkey).
Manis (as Clyde) appeared in Every Which Way But Loose, with Clint Eastwood.
Clint Eastwood appeared in Pale Rider, with Chris Penn.
And Chris Penn appeared in Footloose, with Kevin Bacon.
Friday, January 15, 2010
Sloppy and Floppy
Thursday, January 14, 2010
Start the countdown
Just when I was feeling depressed again about the end of the Rickie Weeks era, a ray of light shone forth from the net. Jemile Weeks, pack your bags and report to Muzzy Field for evaluation.
Tuesday, January 12, 2010
re: mo
"It's facile and leads to self-satisfied conclusions that the data doesn't, actually, support."
this seems to me to be the weakest part of your argument (and it's sort of unfortunately located up in the thesis area). it's actually the "self-satisfied" conclusions that are most supported in the data.
rachel getting married is not a popular movie in compton. it is a very popular movie in lower manhattan. evidence: there is a compton-sized hole in the LA renting patterns map. whereas the lower manhattan map is colored bright red.
brains might be "notoriously poor" at teasing out fine correlations in spatial data, but this one's pretty easy.
can you elaborate on this? there's other stuff in your post, but this seems pretty central and also strikes me as just wrong, regardless of whether or not i like the implications of some of what you're trying to say below (and i think i do).
Monday, January 11, 2010
Why the maps annoy me
The NYT Netflix maps are just the latest in a series of ways geography is being used "interestingly" to make a "point" of some sort that's never actually asserted by the cartographer, but, rather, inferred by the user. This kind of stuff annoys me probably in the same way my using stats annoys scientists (not to say I'm a geographer. I'm not. But I fret about these issues a whole lot). It's facile and leads to self-satisfied conclusions that the data doesn't, actually, support.
Problem 1: The areas are broken up by ZIP code. I think the problems this calls forward are highlighed by the case of Hyde Park, which straddles at least two ZIP codes. You force a kind of "neighborhood" upon the environment that doesn't actually exist there. In some ways this is good, since it randomizes (to a degree) the boundaries. But in other ways it's bad, since 60637 starts to mean something sociologically/anthropologically, not just, you know, postally.
In general, if you're trying to determine something about patterns of some sort, you want to split the study area into quadrats (the number of quadrats determined by comparing the total number of observations to the entire study area). That, of course, requires a certain amount of granularity about the data that netflix might not provide (or the NYT not be interested in working through). But we can't assume that we know something about "a ZIP code" based on the fact that they rented x movie more than y.
(This returns to the one way in which ZIP codes are good, as I hinted above. They are only largely based on preexisting boundaries (of cities, towns, etc.) as opposed to entirely, like ward boundaries. In that sense, they shake up the possible sample you get in each code. The idea of gerrymandering a ZIP code only makes sense in LA.)
So I don't particularly think that ZIP codes are a revealing means of looking into what's going on. Fun, yes. Which leads me to point 2.
Problem 2: It's irresponsible to throw out data like this and let it sit to be played with, in my opinion, without another variable or something to provide context. What the NYT has provided us with is basically a big toy. As I said to Ben, it's interesting, but only like a crossword puzzle is interesting. I love crossword puzzles, and I love doing them, but I don't post about them or forward links to them, since I can't escape Postman's criticism of crossword puzzles as basically what overeducated and understimulated people do out of intellectual boredom. Is anyone surprised that the South Side of Chicago likes Tyler Perry? So what does it mean to point it out, other than to recycle something people would have already pretty much assumed? Without context, the analysis becomes circular, flattering the viewer into making conclusions he or she already suspected.
Problem 2a: There are no numbers that would help us analyze the data better. As in, we have no idea how many Netflix subscribers are in each ZIP code, either in toto, or as a percentage of population. Furthermore, we don't know how many movies, total, get shipped to each ZIP code. Finally, we have no idea how much space is between #1 and #5 in any ZIP code, yet those present fixed differences in coloring. That one lone ZIP code that really loves Rachel Getting Married? Maybe there's just one household in the entire ZIP with a one-at-a-time plan that has a serious erection for TV on the Radio. Again, this is a lack of context.
Problem 3: Autocorrelation. Basically, this means that similar observations tend to cluster. It's kind of a problem for geography, from my understanding, since one is always trying to figure out how much of the data is tainted by autocorrelation. If the point of the maps is to show that, yes, this shit is hell of spatially correlated, well, big deal. Again, there's nothing new in telling me that shit spatially correlated. I know that it's statistically very likely for adjacent ZIP codes to have similar renting patterns. I would like to know, in seeing this data, what kind of built in issues it has with autocorrelation, etc. Here's where something like Moran's I comes in handy. It tells you whether the dataset is correlated or not, allowing you to then more comfortably make conclusions about the distribution of rental patterns.I clean this up in the comments
And then, when there are breaks, like in HP, we're not equipped to understand if that's random or an actual blip, since, again, we're provided with such crappy data. We all *assume* that it's because of the UofC that Slumdoggy was so popular in 60637 (or at least that's what Mario Small suggested in his blog post that alerted me to the site in the first place), but we don't *know* that. And we have no way, with what we're given, to guess how much is the UofC or not.
Which leads, again, to circular and convenient conclusions that flatter our prejudices.
So I've got to go to a booze tasting now, but that's my crank attitude for now.
I'll add one last thing: the eye is a bad mathematician, and it is way too eager to see patterns where there are none, which is why it's so easy to lie with maps. Of course, I understand that this is all fun and a way to burn some time (see Postman and crosswords above), but I've seen the explosion of this kind of mapping shit lately as a threat to real geospatial analysis. I dunno. Forward this on to Conzen and see if he thinks I'm crazy. I'm willing to be told I am. But it doesn't change the fact that, in my work, I have to compete with jokes like the google books map that accompanies every novel.
OKOKK... last thing... What I would've liked is a per movie distribution as a hotzone, so, not bounded by ZIP codes. That would've been more interesting and sociologically useful, since it would help account for the variations in potential renting diversity within each ZIP.
Problem 1: The areas are broken up by ZIP code. I think the problems this calls forward are highlighed by the case of Hyde Park, which straddles at least two ZIP codes. You force a kind of "neighborhood" upon the environment that doesn't actually exist there. In some ways this is good, since it randomizes (to a degree) the boundaries. But in other ways it's bad, since 60637 starts to mean something sociologically/anthropologically, not just, you know, postally.
In general, if you're trying to determine something about patterns of some sort, you want to split the study area into quadrats (the number of quadrats determined by comparing the total number of observations to the entire study area). That, of course, requires a certain amount of granularity about the data that netflix might not provide (or the NYT not be interested in working through). But we can't assume that we know something about "a ZIP code" based on the fact that they rented x movie more than y.
(This returns to the one way in which ZIP codes are good, as I hinted above. They are only largely based on preexisting boundaries (of cities, towns, etc.) as opposed to entirely, like ward boundaries. In that sense, they shake up the possible sample you get in each code. The idea of gerrymandering a ZIP code only makes sense in LA.)
So I don't particularly think that ZIP codes are a revealing means of looking into what's going on. Fun, yes. Which leads me to point 2.
Problem 2: It's irresponsible to throw out data like this and let it sit to be played with, in my opinion, without another variable or something to provide context. What the NYT has provided us with is basically a big toy. As I said to Ben, it's interesting, but only like a crossword puzzle is interesting. I love crossword puzzles, and I love doing them, but I don't post about them or forward links to them, since I can't escape Postman's criticism of crossword puzzles as basically what overeducated and understimulated people do out of intellectual boredom. Is anyone surprised that the South Side of Chicago likes Tyler Perry? So what does it mean to point it out, other than to recycle something people would have already pretty much assumed? Without context, the analysis becomes circular, flattering the viewer into making conclusions he or she already suspected.
Problem 2a: There are no numbers that would help us analyze the data better. As in, we have no idea how many Netflix subscribers are in each ZIP code, either in toto, or as a percentage of population. Furthermore, we don't know how many movies, total, get shipped to each ZIP code. Finally, we have no idea how much space is between #1 and #5 in any ZIP code, yet those present fixed differences in coloring. That one lone ZIP code that really loves Rachel Getting Married? Maybe there's just one household in the entire ZIP with a one-at-a-time plan that has a serious erection for TV on the Radio. Again, this is a lack of context.
And then, when there are breaks, like in HP, we're not equipped to understand if that's random or an actual blip, since, again, we're provided with such crappy data. We all *assume* that it's because of the UofC that Slumdoggy was so popular in 60637 (or at least that's what Mario Small suggested in his blog post that alerted me to the site in the first place), but we don't *know* that. And we have no way, with what we're given, to guess how much is the UofC or not.
Which leads, again, to circular and convenient conclusions that flatter our prejudices.
So I've got to go to a booze tasting now, but that's my crank attitude for now.
I'll add one last thing: the eye is a bad mathematician, and it is way too eager to see patterns where there are none, which is why it's so easy to lie with maps. Of course, I understand that this is all fun and a way to burn some time (see Postman and crosswords above), but I've seen the explosion of this kind of mapping shit lately as a threat to real geospatial analysis. I dunno. Forward this on to Conzen and see if he thinks I'm crazy. I'm willing to be told I am. But it doesn't change the fact that, in my work, I have to compete with jokes like the google books map that accompanies every novel.
OKOKK... last thing... What I would've liked is a per movie distribution as a hotzone, so, not bounded by ZIP codes. That would've been more interesting and sociologically useful, since it would help account for the variations in potential renting diversity within each ZIP.
the layout was killing me
so i changed it
does anyone have the projections/predictions from 2009? i want to know who didn't believe in me (other than myself)
also, i am tempted to post a poll on "which ridiculous statistical outlier was most relevant to pete's championship? A) jason bartlett B) jason bartlett C) jason bartlett D) jair jurrjens"
does anyone have the projections/predictions from 2009? i want to know who didn't believe in me (other than myself)
also, i am tempted to post a poll on "which ridiculous statistical outlier was most relevant to pete's championship? A) jason bartlett B) jason bartlett C) jason bartlett D) jair jurrjens"
Sunday, January 10, 2010
Plot example, lobbying stories
Here's one I did with plot for a chapter in my diss. Hugo Black chaired a pretty big investigation into lobbying in 1935 and 1936; so big it drove a spike in news coverage. I counted the number of hits for ProQuest searches of "lobbying." There's another version, where I try to control for the total number of stories. The shape ends up the same. Why do I think we're going to end up with a lot of graphs heading into this baseball draft?
poor pierre bordieu
you died before the era of google maps + online data feeds.
UPDATE: also see this img:
my fave find in the whole thing is that in one zip code in Long Island, in the shitty inner burb belt of sad pudgy back-office people who take LIRR to midtown, PINEAPPLE EXPRESS is beet-red. medical marijuana's time has come! depression is real!
Saturday, January 09, 2010
More on points
Average points per NFL season, top 10
1. 2008
2. 1983
3. 2007
4. 2002
5. 2004
6. 1995
7. 1985
8. 2009
9. 1998
10. 1984
1. 2008
2. 1983
3. 2007
4. 2002
5. 2004
6. 1995
7. 1985
8. 2009
9. 1998
10. 1984
Golden Age of Offense
Yeah, it's football so maybe it shouldn't be on here, but is anyone going to return to the yahoo board ever again? I went to admire the additions to my trophy case, and saw mcard's post about Fred Jackson and the bumper crop of all-purpose yard machines this season. It struck me that NFL offenses have been out of control, especially QBs. 4,000 yards doesn't seem like any big deal and I just found this link to confirm my suspicion:
http://www.profootballhof.com/history/release.aspx?release_id=1330
A new record: ten different QBs went over 4,000. The previous two records, seven and six QBs, were set in 2007 and 2008, respectively.
In terms of total yards, average for the top 15 teams, and number over 6,000 yards, 2002-2009
2002: 5778, 4
2003: 5577, 1
2004: 5809, 5
2005: 5573, 1
2006: 5615, 3
2007: 5680, 1
2008: 5764, 3
2009: 5919, 6
Average total points, top 15 teams, and number over 450, 1999-2009
1999: 387, 1
2000: 393, 3
2001: 368, 1
2002: 398, 2
2003: 398, 1
2004: 403, 2
2005: 391, 1
2006: 387, 1
2007: 415, 3
2008: 407, 1
2009: 412, 4
1984: 396, 2 (Marino's insane year)
Be good to do this for all the teams (to see if maybe the top fifteen are just taking on a bigger share) and take it back a lot further than ten years, but it seems offense is on an uptick. This might help explain why there was so much parity in our fantasy football league this season; with a lot more points and yards to go around, the talent pool was a bit deeper than some other years. That's my hypothesis for now.
http://www.profootballhof.com/history/release.aspx?release_id=1330
A new record: ten different QBs went over 4,000. The previous two records, seven and six QBs, were set in 2007 and 2008, respectively.
In terms of total yards, average for the top 15 teams, and number over 6,000 yards, 2002-2009
2002: 5778, 4
2003: 5577, 1
2004: 5809, 5
2005: 5573, 1
2006: 5615, 3
2007: 5680, 1
2008: 5764, 3
2009: 5919, 6
Average total points, top 15 teams, and number over 450, 1999-2009
1999: 387, 1
2000: 393, 3
2001: 368, 1
2002: 398, 2
2003: 398, 1
2004: 403, 2
2005: 391, 1
2006: 387, 1
2007: 415, 3
2008: 407, 1
2009: 412, 4
1984: 396, 2 (Marino's insane year)
Be good to do this for all the teams (to see if maybe the top fifteen are just taking on a bigger share) and take it back a lot further than ten years, but it seems offense is on an uptick. This might help explain why there was so much parity in our fantasy football league this season; with a lot more points and yards to go around, the talent pool was a bit deeper than some other years. That's my hypothesis for now.
Friday, January 08, 2010
Thursday, January 07, 2010
zack greinke
this is true. we are hit number 37 on the google image results for david wright.
carter, i will support your ongoing monetization efforts. not that you were ever in doubt.
Wednesday, January 06, 2010
I shot at things with things
So even discounting the throws from his knees or foul territory... that one where he basically waits for a ball slammed off home plate to peg the runner. ¡Que calor!
Monetize Tab
What?! There is a monetize tab on blogger? Why didn't anyone tell me about this! I need everyone's proxy to set this up. Or maybe I should set up a Delaware corporation. Come on people: You wouldn't let me monetize keeper slots back in the day, so at least let me have this.
David Wright Page
I dont know if i gave anyone else access to the google analytics but the David Wright page has had almost 3000 hits in the past 24 months. we need some ads.
einardiaz.blogspot.com - 9000 hits and counting.
einardiaz.blogspot.com - 9000 hits and counting.
China Will Crush Us All
A question
First, fill out the survey.
Next, how much respect should you lose for someone if they totally tank a world-flags/geography quiz limited to Europe and North America and some Asia? Like even 5-10 current-events prompts don't get them to guess the country or capital?
We played as a group, and the people who were having some difficulty even started being blown away by the total inability of two of the players. Like, "I don't know if we can still be friends." But since I know that this sort of stuff was my bread and butter as a kid, I can't gauge how much of this stuff is actually common knowledge among a certain type of person.
Next, how much respect should you lose for someone if they totally tank a world-flags/geography quiz limited to Europe and North America and some Asia? Like even 5-10 current-events prompts don't get them to guess the country or capital?
We played as a group, and the people who were having some difficulty even started being blown away by the total inability of two of the players. Like, "I don't know if we can still be friends." But since I know that this sort of stuff was my bread and butter as a kid, I can't gauge how much of this stuff is actually common knowledge among a certain type of person.
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