Probably a bad sign when I haven't posted anything for a week, and I'm about to go on vacation for another week. A quick glance at the headlines:
Sports: The four highest paid players in baseball are Alex Rodriguez, Derek Jeter, CC Sabathia and Mark Teixeira. They will make over $100,000,000 next year. All four play for the New York Yankees.
Feel good story that isn't news but will be reported as news anyway: I experienced a Christmas Miracle yesterday. I went to Walmart looking for a few items and, predictably, only found 1 of them. I went to the front of the store to purchase my one item, only to find the typical mess of long lines of people with heaped up shopping carts. I picked a line and got prepared for the long wait, only to have two different people in front of me with carts piled high invite me to go infront of them. I ended up with almost no wait! In Walmart! 3 days before Christmas! And nice people exist in Walmart! Amazing!
Thursday, December 18
I've competed in a tractor pull. I hadn't thought about this in years, but about 15 years ago, I drove a little tractor in the competition. I didn't win, nor really have any clue what was going on, but I did it. And how many people do you know who have competed in a tractor pull? I bet you wouldn't have thought I was the one, huh?
(The tractor was much smaller than anything I was able to find on youtube.)
(The tractor was much smaller than anything I was able to find on youtube.)
Tuesday, December 16
Sunday, December 14
Beam Me Up
About a decade ago, while coming home to visit my family, I was stopped as I got out of the car by an older man who lived a few doors down the street from my parents. (He might still be there, I'm not sure.) He came up to me and said something like "Scott, how is your brother Clark doing? I remember when he was just a little kid . . . blah blah blah . . ." Basically, he invented an older brother for me, figured I was that brother and that my name was Scott. Weird.
Fast forward a decade. There is an older guy in our new ward who keeps calling me Scott. I was well introduced correctly when we first me, and he's called me Clark successfully multiple times. But he keeps reverting back to Scott, even after being corrected a few times. And he doesn't even notice when he does it.
So, I guess I must look like a Scott or something.
Fast forward a decade. There is an older guy in our new ward who keeps calling me Scott. I was well introduced correctly when we first me, and he's called me Clark successfully multiple times. But he keeps reverting back to Scott, even after being corrected a few times. And he doesn't even notice when he does it.
So, I guess I must look like a Scott or something.
Friday, December 12
Still Using Zebras
This blog is a bit over 2 years old, and has nearly 400 posts. Nearly all of them have been long since forgotten. However, this post from a year ago today is easily the most visited post this month. Suzanne's response on her blog seems to be equally hot. The posts are about an old Christmas song called "Santa's Using Zebras Now". And it's virtually unknown and nearly un-googlable. Googling "Santa's Using Zebras Now" gives Suzanne's blog as the first hit and mine as the 3rd. The second reference is to someone posting the lyrics which they copied off of Suzanne's comment on my cousins blog (6th google hit on the search). (I know this, because they reference the song as an "annual Blockburger favorite," a line from my her comment, but can't figure out what a 'Blockburger' is. Apparently no one has heard of those, either.)
The last two days alone have had six visitors to my blog looking for the song. They come from Greensboro, Memphis, Salt Lake, Schaumburg Ill, Lincoln, Ancorage and Washingtong. (As I was typing that sentence I just got another visitor from Riverside.)
So, if you're looking for the song, you're not alone. And you're also not alone in not being able to find a copy. Some people have offered some help on Suzanne's blog. (Maybe we all need to convince Suzanne to get over to our parents house and track the music down. It might be the world's last remaining copy!)
The last two days alone have had six visitors to my blog looking for the song. They come from Greensboro, Memphis, Salt Lake, Schaumburg Ill, Lincoln, Ancorage and Washingtong. (As I was typing that sentence I just got another visitor from Riverside.)
So, if you're looking for the song, you're not alone. And you're also not alone in not being able to find a copy. Some people have offered some help on Suzanne's blog. (Maybe we all need to convince Suzanne to get over to our parents house and track the music down. It might be the world's last remaining copy!)
Tuesday, December 9
Bimodal Twilight
I have not read, nor do I plan to read any of the Twilight books. I have not seen, nor do I plan to see any of the Twilight movies. If you love the books, Alex can provide you with all you could ever want on that topic. For the rest of us, I will not fan the flames by providing any snide remarks on the topic, nor poking fun at the story in any way.
My real purpose in bringing this up is to talk about normal distributions. Thrilling topic, isn't it? You're all quivering with anticipation I'm sure. (Or are you quivering because of my luminous marble-like pasty white complexion?)If we were to go measure something like . . . say . . . the mass of all your T-shirts, what would we expect to find? Logic would tell us that they'll weigh roughly the same, but there will be some variation. Some will be worn out and thin, and weigh less. Others will be a size to large, meaning more fabric (plus, still in mint condition because you don't want to wear a big ol' T-shirt) so they'll weigh more. If we were to graph the results, we would likely see a 'normal' distribution. We call this 'normal' because so much data comes out looking like this. The size of leaves on a tree. The height of 2 year-olds. The distance you can throw a baseball. Anything where there is an expected value, and then some events that fall a little beyond or a little short of that.
Now, many things are not 'normal'. If we were to expand our measurement to the weight of all your shirts, we might find it to be 'bimodal'. (Remember, the 'mode' of a data set is the single value that is most common. To be bimodal means there are two different values which are both significant maxiumums (though one will still likely be larger).) In the case of the shirts, we would expect that T-shirts are light, but that your vast collection of sweaters would introduce another graphical hump. Lots of things are also bimodal, typically things that depend on some factor with two possible outcomes that influnces the data. The weight of a group of people, for example. We would expect to see a peak where many of the women fall, and then a separate peak higher up for the men.
Ok, that was all warm-up for what I really wanted to get at. What would we expect for a movie rating distribution? At first thought, maybe a normal distribution. Imagine seeing a movie with a very large group of friends and discussing it afterwards. You might expect that many people would rate it 'ok' with a few that liked it more, or a few that liked it less. If that's what actually happened, then maybe the movie you saw was 'I Am Legend'.
But when you think about it, this isn't really typical of peoples resonses. Usually a bunch of people think a movie is 'good' or 'ok' but there are a few who really, really love it. Such is the case with 'Ice Princess' which is nicely bimodal.
Or maybe you've seen a movie where many of the people thought it was ok, but some of them really liked it, while others really hated it. That might be 'Four Christmases'. (What is this? Trimodal?)
But, I think it is really interesting (and likely unique) to find a movie with no middle ground. You either love it or hate it. And that, is Twilight. I think what we have here is the data from all the women who went to go see it, as well as the results from their fathers/boyfriends/husbands. ;)
All movie data sets came from imdb.com
My real purpose in bringing this up is to talk about normal distributions. Thrilling topic, isn't it? You're all quivering with anticipation I'm sure. (Or are you quivering because of my luminous marble-like pasty white complexion?)If we were to go measure something like . . . say . . . the mass of all your T-shirts, what would we expect to find? Logic would tell us that they'll weigh roughly the same, but there will be some variation. Some will be worn out and thin, and weigh less. Others will be a size to large, meaning more fabric (plus, still in mint condition because you don't want to wear a big ol' T-shirt) so they'll weigh more. If we were to graph the results, we would likely see a 'normal' distribution. We call this 'normal' because so much data comes out looking like this. The size of leaves on a tree. The height of 2 year-olds. The distance you can throw a baseball. Anything where there is an expected value, and then some events that fall a little beyond or a little short of that.
Now, many things are not 'normal'. If we were to expand our measurement to the weight of all your shirts, we might find it to be 'bimodal'. (Remember, the 'mode' of a data set is the single value that is most common. To be bimodal means there are two different values which are both significant maxiumums (though one will still likely be larger).) In the case of the shirts, we would expect that T-shirts are light, but that your vast collection of sweaters would introduce another graphical hump. Lots of things are also bimodal, typically things that depend on some factor with two possible outcomes that influnces the data. The weight of a group of people, for example. We would expect to see a peak where many of the women fall, and then a separate peak higher up for the men.
Ok, that was all warm-up for what I really wanted to get at. What would we expect for a movie rating distribution? At first thought, maybe a normal distribution. Imagine seeing a movie with a very large group of friends and discussing it afterwards. You might expect that many people would rate it 'ok' with a few that liked it more, or a few that liked it less. If that's what actually happened, then maybe the movie you saw was 'I Am Legend'.
But when you think about it, this isn't really typical of peoples resonses. Usually a bunch of people think a movie is 'good' or 'ok' but there are a few who really, really love it. Such is the case with 'Ice Princess' which is nicely bimodal.
Or maybe you've seen a movie where many of the people thought it was ok, but some of them really liked it, while others really hated it. That might be 'Four Christmases'. (What is this? Trimodal?)
But, I think it is really interesting (and likely unique) to find a movie with no middle ground. You either love it or hate it. And that, is Twilight. I think what we have here is the data from all the women who went to go see it, as well as the results from their fathers/boyfriends/husbands. ;)
All movie data sets came from imdb.com
Sunday, December 7
MNC
Oklahoma and Florida will be playing each other for the mythical national championship next month. According to ESPN, OU and Florida have never played a game against each other. And that is why college football his forever doomed to championship disputes. Even with a playoff, ranking and seeding teams would still factor in, and you just can't do it when teams don't play very many games and don't play each other. Apparently, OU and Florida can only find time in the schedules for each other every . . . oh, say, 100 years. They play conference games, and then are busy playing their in-state non-conference rivals, or their local crappy teams for easy wins.
Wednesday, December 3
Chistmas Songs
Two years ago, I complained about the general low quality of Christmas music. The talent level required to get music on the radio seems to drop significantly if it is December. I don't like that. (I'm sure that this has nothing to do with any donkey songs that were re-brought to my attention recently.)
This year, I hope to bring to all of our lives some good Christmas music. If you've got songs you wish to nominate, go for it.
The first song to be high lighted is "God Rest Ye Merry Gentlemen / We Three Kings" by Barenaked Ladies and Sarah McLachlan. The album "Barenaked for the Holidays" is in general quite good, and this song is excellent. Two songs that are individually terrific, and interesting interpretation, a good pairing of performers, and a snappy beat.
This year, I hope to bring to all of our lives some good Christmas music. If you've got songs you wish to nominate, go for it.
The first song to be high lighted is "God Rest Ye Merry Gentlemen / We Three Kings" by Barenaked Ladies and Sarah McLachlan. The album "Barenaked for the Holidays" is in general quite good, and this song is excellent. Two songs that are individually terrific, and interesting interpretation, a good pairing of performers, and a snappy beat.
Monday, December 1
Football
"I'm looking forward to the inevitable upcoming post on the BCS, in light of the injustice Texas endured this weekend."
I'm not sure if Adam predicted the future here, or I'm simply giving the readers what they want. (Pay attention to this reader(s), ask and ye might just receive.)
For those of you who are less informed, but want to know what Adam is talking about here, Oklahoma (OU) gets to go to the Big XII championship game rather than Texas (UT), despite Texas beating OU on a neutral field. This is because the tie was broken by OU being very slightly ahead of UT in this weeks BCS rankings. (What are the odds that anyone reading this didn't know this, yet actually cares about the subject? Slim.)
Now, I've never really heard Adam be much of a UT fan, but he was raised (if not born) in Texas, so I assume that he'll be disappointed with me when I say that I think the end result (OU over UT) was right, even if the course to get there was a bit screwy.
First, it is important to remember that it's not like the BCS tie breaker is the first and only tie breaking method used by the Big 12 conference. In the event of a 2 way tie, the head to head game is the tie breaker, which makes sense. But, this was not a 2 way tie. It's been quickly forgotten that Texas Tech (TT) also has a single loss this season. TT beat UT, UT beat OK and OK beat TT. Other than that, each team is undefeated. So, unscrambling things is a bit trickier. In the event of a 3 (or more) way tie, the Big 12 tiebreaker procedure calls for a comparison of:
1. Teams head to head record (each 1-1)
2. Teams record w/in their division (undefeated).
3. Records against next highest teams in division starting w/ #4. (undefeated)
4. Reocrds against all common opponents. (undefeated)
5. BCS ranking. (OU wins)
6. Winning percentage (tie).
7. Winner chosen by draw.
So, if we had chosen to skip the BCS mess, the winner would have been selected by picking names out of a hat, or ping-pong balls, or a three sided coin. I don't think that would be better. Its a tricky thing, deciding three way ties. I'd be curious for suggestions of what specific measurable metric should be used instead of the BCS. (Poll 100 people?, time of possession?, turnover margin?, graduation rate?, winner-take-all game of Battleship?) Remember, that people are always loathe to use margin of victory, as it encourages running up the score.
But, since I already said I agree with the selection of OU (if not the method, though I don't particularly have a better one) I will now support that claim. First off, this blog does a decent job of comparing UT, OU and TTs games against each other. Basically, OU came out way ahead on net points and net yards between the two games. Analyzing the games would show that perhaps the score was "run up" a bit in the OU/TT game, you can't fault a team for wanting to build up a large cushion in the first half against one of the most explosive offenses in the nation.
OU likewise wins a schedule comparison, in my opinion. This is where TT gets dropped from the conversation. They beat Eastern Washington, UMass, Nevada and SMU. That's 2 I-AA opponents, an ok WAC team and a bad C-USA team. About 50 or 60 teams in the nation could expect to go undefeated in those games. UT beat FAU, UTEP, Arkansas and Rice. While none of those teams are out right horrible, none of them are all that good either. OU, played Chattanooga, Cincinnati, Washington and TCU. Two of those teams (Chattanooga, and UW) are just terrible, but Cincinnati (10-2, BCS #13) and TCU (10-2, BCS #11) are pretty good. A schedule of 2 good teams and 2 terrible teams is tougher than 4 so-so teams. A #25 team would expect to beat all 4 of UT's non-conference opponents, whereas they would likely be glad to finish 3-1 against OU's opponents.
(The schedules also show that TT had to go to OT to beat Nebraska, UT had a single close game vs OSU, and OU has no win of less than 14 points.)
So, there you go. Really, the big looser in all of this is Oklahoma State, which is probably a top 20 team, maybe a top 15 team, yet couldn't do better than 4th place in their division of their conference. Ironically, their chances of going to a BCS game would have been better if they had moved to the MWC. Going undefeated against TCU, BYU and Utah is easier than against OU, UT and TT.
Addendum: I meant to say this initially, but forgot, what with Firefox crashing a few times during my post. How can I support OU when UT beat them, head to head? (Though, TT beat UT, and OU beat TT, but OU lost to UT, even though UT lost to TT . . . . ) It's all about sampling size. One game is a really crummy way to figure out if one team is "better" than another. 12 games is still pretty crummy, but that is something we can actually work with. This is the underlying difficulty with college football. 119 teams, and they only play 12-13 games each. When faced with this 3-way tie connundrum, I believe it is best to use the entire season as an attempt to gauge which team really is the "best". It's a poor system, but it's all we've got to work with.
I'm not sure if Adam predicted the future here, or I'm simply giving the readers what they want. (Pay attention to this reader(s), ask and ye might just receive.)
For those of you who are less informed, but want to know what Adam is talking about here, Oklahoma (OU) gets to go to the Big XII championship game rather than Texas (UT), despite Texas beating OU on a neutral field. This is because the tie was broken by OU being very slightly ahead of UT in this weeks BCS rankings. (What are the odds that anyone reading this didn't know this, yet actually cares about the subject? Slim.)
Now, I've never really heard Adam be much of a UT fan, but he was raised (if not born) in Texas, so I assume that he'll be disappointed with me when I say that I think the end result (OU over UT) was right, even if the course to get there was a bit screwy.
First, it is important to remember that it's not like the BCS tie breaker is the first and only tie breaking method used by the Big 12 conference. In the event of a 2 way tie, the head to head game is the tie breaker, which makes sense. But, this was not a 2 way tie. It's been quickly forgotten that Texas Tech (TT) also has a single loss this season. TT beat UT, UT beat OK and OK beat TT. Other than that, each team is undefeated. So, unscrambling things is a bit trickier. In the event of a 3 (or more) way tie, the Big 12 tiebreaker procedure calls for a comparison of:
1. Teams head to head record (each 1-1)
2. Teams record w/in their division (undefeated).
3. Records against next highest teams in division starting w/ #4. (undefeated)
4. Reocrds against all common opponents. (undefeated)
5. BCS ranking. (OU wins)
6. Winning percentage (tie).
7. Winner chosen by draw.
So, if we had chosen to skip the BCS mess, the winner would have been selected by picking names out of a hat, or ping-pong balls, or a three sided coin. I don't think that would be better. Its a tricky thing, deciding three way ties. I'd be curious for suggestions of what specific measurable metric should be used instead of the BCS. (Poll 100 people?, time of possession?, turnover margin?, graduation rate?, winner-take-all game of Battleship?) Remember, that people are always loathe to use margin of victory, as it encourages running up the score.
But, since I already said I agree with the selection of OU (if not the method, though I don't particularly have a better one) I will now support that claim. First off, this blog does a decent job of comparing UT, OU and TTs games against each other. Basically, OU came out way ahead on net points and net yards between the two games. Analyzing the games would show that perhaps the score was "run up" a bit in the OU/TT game, you can't fault a team for wanting to build up a large cushion in the first half against one of the most explosive offenses in the nation.
OU likewise wins a schedule comparison, in my opinion. This is where TT gets dropped from the conversation. They beat Eastern Washington, UMass, Nevada and SMU. That's 2 I-AA opponents, an ok WAC team and a bad C-USA team. About 50 or 60 teams in the nation could expect to go undefeated in those games. UT beat FAU, UTEP, Arkansas and Rice. While none of those teams are out right horrible, none of them are all that good either. OU, played Chattanooga, Cincinnati, Washington and TCU. Two of those teams (Chattanooga, and UW) are just terrible, but Cincinnati (10-2, BCS #13) and TCU (10-2, BCS #11) are pretty good. A schedule of 2 good teams and 2 terrible teams is tougher than 4 so-so teams. A #25 team would expect to beat all 4 of UT's non-conference opponents, whereas they would likely be glad to finish 3-1 against OU's opponents.
(The schedules also show that TT had to go to OT to beat Nebraska, UT had a single close game vs OSU, and OU has no win of less than 14 points.)
So, there you go. Really, the big looser in all of this is Oklahoma State, which is probably a top 20 team, maybe a top 15 team, yet couldn't do better than 4th place in their division of their conference. Ironically, their chances of going to a BCS game would have been better if they had moved to the MWC. Going undefeated against TCU, BYU and Utah is easier than against OU, UT and TT.
Addendum: I meant to say this initially, but forgot, what with Firefox crashing a few times during my post. How can I support OU when UT beat them, head to head? (Though, TT beat UT, and OU beat TT, but OU lost to UT, even though UT lost to TT . . . . ) It's all about sampling size. One game is a really crummy way to figure out if one team is "better" than another. 12 games is still pretty crummy, but that is something we can actually work with. This is the underlying difficulty with college football. 119 teams, and they only play 12-13 games each. When faced with this 3-way tie connundrum, I believe it is best to use the entire season as an attempt to gauge which team really is the "best". It's a poor system, but it's all we've got to work with.
News Flash
You heard it here first, folks, Julia now has 2 teeth.
Couple that with a slight cold, and a trip to a strange place and Shannon and I got to hold Julia A LOT all weekend long.
Couple that with a slight cold, and a trip to a strange place and Shannon and I got to hold Julia A LOT all weekend long.
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