14 March 2010: Swim Progress Continues

Workout notes 7050 swim (4 miles) in 2:02:32; my 1000 to 6500 5K split was 1:35:08, about 40 seconds slower than my PB. I averaged 17:22 per 1000.

Here is my workout in table form:

14 March 2010	7 March 2010	17 Dec. 2009	1 Jan. 2010	17Jan. 2010	28 Feb. 2010
1:35:17 5k	1:37:01 (5k)	1:36:23	1:38:27	1:34:29	1:35:47
17:41 (+19)	17:39 (-1)	17:42 (+10)	17:52 (-2)	17:40 (+29)	17:33 (+8)
17:15 (-7)	17:35 (-5)	17:08 (-24)	17:36 (-18)	16:56 (-15)	17:11 (-14)
17:18 (-4)	17:36 (-4)	17:14 (-18)	17:45 (-9)	16:53 (-18)	17:14 (-11)
17:13 (-9)	17:41 (+1)	17:36 (+4)	17:48 (-6)	17:00 (-11)	17:26 (+1)
17:05 (-17)	17:38 (-2)	17:43 (+11)	18:02 (+8)	17:18 (+7)	17:32 (+7)
8:42	8:49	8:57 (+11)	9:22 (+25)	8:40 (+4)	8:49( +6)
17:27 (+5)	17:40 (0)	5k to 6k
17:35 (+13)	17:50 (+10)	6K to 7K
0:55	2:02:32	0:53	2:04:34

Past data: last week, previous distance swims.

I was aided by two guys jumping into the lanes on either side of me; one swam at roughly my pace and the other was much faster. This happened at about 3000-3500 into the swim.

Other factors: no lifting yesterday and last night, my injury did NOT wake me up. It was almost as if the gentle walking between airport gates (when I picked my daughter up) made it feel better last night.

Overall I feel good about the effort, though I am only about 63 percent of where I want to be. My goal is 11000 yards or 10000 meters and I have about 15 weeks to get there.

13 March 2010: PM

Olivia is here! Note: Chicago Midway Airport was relatively uncrowded; little if any lines at the counters and almost no trouble getting through security.

Posts
Education You can’t make this up:

Like most colleges, my college uses an automatic plagiarism checker for all assignments. When I see an assignment, it comes with a report from Turnitin.com, which gives me a percentage of non-original content. Per the sales-team-I-mean-administration, anything below 25% is acceptable, anything above warrants a second look. If I suspect a student of plagiarizing, I am to forward the matter to an office that deals directly with this.

What’s the problem, you ask?

Let me tell you a little bit about Frank the Fuckhead. He has turned in three assignments. Each had a originality score between 25% and 45%. Each time, I found that he had copied large chunks of information from the Internet. The first time, I gave him an F and let him resubmit. He resubmitted the exact. same. thing. I turned him over to the office meant to deal with the matter. They, in turn, admonished me for not being “student centered.”

This is not as far fetched as it sounds.

Animal Camouflage via Conservation Report
The latest.

My all time favorite.

Statistics and science Perhaps the headline is sensationalistic but the article is interesting reading. Here is a bit of it:

Statistical significance is a phrase that every science graduate student learns, but few comprehend. While its origins stretch back at least to the 19th century, the modern notion was pioneered by the mathematician Ronald A. Fisher in the 1920s. His original interest was agriculture. He sought a test of whether variation in crop yields was due to some specific intervention (say, fertilizer) or merely reflected random factors beyond experimental control.

Fisher first assumed that fertilizer caused no difference — the “no effect” or “null” hypothesis. He then calculated a number called the P value, the probability that an observed yield in a fertilized field would occur if fertilizer had no real effect. If P is less than .05 — meaning the chance of a fluke is less than 5 percent — the result should be declared “statistically significant,” Fisher arbitrarily declared, and the no effect hypothesis should be rejected, supposedly confirming that fertilizer works.

Fisher’s P value eventually became the ultimate arbiter of credibility for science results of all sorts — whether testing the health effects of pollutants, the curative powers of new drugs or the effect of genes on behavior. In various forms, testing for statistical significance pervades most of scientific and medical research to this day.

But in fact, there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke. Fisher’s method offers no way to know which is which. On the other hand, if a study finds no statistically significant effect, that doesn’t prove anything, either. Perhaps the effect doesn’t exist, or maybe the statistical test wasn’t powerful enough to detect a small but real effect.