The Shutdown Corner, a Yahoo! sports blog notes that the redskins will play their sixth consecutive game against a winless opponent. Quite impressive. In the post they note that the chances of this happening are 1 in 32,768. I have some comments:

I think what they mean to say is that given the Redskins schedule this year and assuming each of their opponents has a 50% chance of winning each of their games the chances of this happening are 1 in 32,768. (That calculation checks out.)

However, the assumption that any of the redskins opponents has a 50% chance of winning their games is laughable at best (i.e. Lions, Bucs, Chiefs). If we re-do this calculation with last years respective winning percentages for these teams the chances are only about 1 in 1,703. ((14/16)*(7/16)^3*(4/16)^3*(14/16)^5=0.000587). But the bucs and panthers are much worse than last year, so the chances are probably a bit larger than 1 in 1,703.

On the other hand, for this to happen to a random team with a random schedule is very unlikely. Evidence of this is that it has never happened in NFL history before, as noted in that blog post.

So while the Redskin’s feat is impressive (or depressing?), I think they got the numbers wrong.

Cheers.

This. Is. Awesome.

Google is using aggregated counts of search terms to predict the prevalence of flu.

They say:
“We’ve found that certain search terms are good indicators of flu activity. Google Flu Trends uses aggregated Google search data to estimate current flu activity around the world in near real-time.”

Google Flu Trends. Watch the video.

Cheers.

So I’m slowly making my way through chapters 15-18 of Probability Essentials by Jacod and Protter and the introduction to chapter 16 mentions that C.F. Gauss used to be on the old German 10 Deutche Mark along with the normal pdf.

Here is a picture.

Cheers.

A few days ago as I was driving to work (ok, i don’t really have a job…..school), I heard on the radio that New York health care workers were protesting in Albany about being forced to get the regular seasonal flu vacine and then the H1N1 vaccine or be fired. Their argument that the vaccine has not been fully tested and may be unsafe. So is it safe and worth it? Almost definately yes.

From that same article: “State Health Commissioner Richard Daines MD, recently said in an open letter to health care workers, urging them not to resist, ‘Given the outstanding efficacy and safety record of approved influenza vaccines, our overriding concern then, as health care workers, should be the interests of our patients, not our own sensibilities about mandates.'”

Further, the CDC offers General Questions and Answers on 2009 H1N1 Influenza Vaccine Safety. From there:
Will the 2009 H1N1 influenza vaccines be safe?
“We expect the 2009 H1N1 influenza vaccine to have a similar safety profile as seasonal flu vaccines, which have a very good safety track record. Over the years, hundreds of millions of Americans have received seasonal flu vaccines. The most common side effects following flu vaccinations are mild, such as soreness, redness, tenderness or swelling where the shot was given. The Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA) will be closely monitoring for any signs that the vaccine is causing unexpected adverse events and we will work with state and local health officials to investigate any unusual events.”

Past seasonal flu vaccines have been very successful in preventing the flu. See, for instance, the article from the New England Journal of Medicine, “The Effectiveness of Vaccination against Influenza in Healthy, Working Adults.” There is no reason to believe this flu should be different with regards to the efficacy of the vaccine. So the benefits of receiving the flu vaccine are relatively high.

Alternatively, some people are worried about Guillain-Barre Syndrome as a result of the Swine Flu vaccine. The CDC has this to say about Seasonal Flu and Guillain-Barré Syndrome (GBS). An article, “Vaccines and Guillain-Barré syndrome,” says in its abstract: “There is little evidence to support a causal association with most vaccines. The evidence for a causal association is strongest for the swine influenza vaccine that was used in 1976-77. Studies of influenza vaccines used in subsequent years, however, have found small or no increased risk of GBS.” Another article, “Guillain-Barré syndrome following influenza vaccination“, concludes that “From 1990 to 2003, VAERS reporting rates of GBS after influenza vaccination decreased. The long onset interval and low prevalence of other preexisting illnesses are consistent with a possible causal association between GBS and influenza vaccine. These findings require additional research, which can lead to a fuller understanding of the causes of GBS and its possible relationship with influenza vaccine.” The rates of infection were extremely low. They note, “The annual reporting rate decreased 4-fold from a high of 0.17 per 100,000 vaccinees in 1993-1994 to 0.04 in 2002-2003 (P<.001)." So there MAY be a causal relationship, but the risk is extremly low relative to the benefits. The deciusion will ultiamtely depend on how you define your loss function. And, as a wise friend once told me, everyone has a different loss function.

So everyone has to weight the upside of almost definately preventing the flu versus the downside of side effects of the drug which are usually mild. Severe reactions MAY cause GBS, but this is extremly rare. You are much, much more likely to be killed by the flu than GBS caused by a swine flu vaccine, especially if you are in one of the at risk groups for the flu.

Cheers.

Also, if interested, here is some good information on clinical trials.

Cheers.

A world first: Vaccine helps prevent HIV infection

Some more details about the trial.

Cheers.

Apparently there is something called “follow Friday” on Twitter. NISSSAMSI suggested StatsInTheWild last week.

Tweet:
“NISSSAMSI #FF @StatsInTheWild @tomanalytics @MathIsMyLife @numberonics @sallycmorton @Ron_Wasserstein @StatisticsNews @StatsMan2886 @statgrrl”

sallycmorton is the president of the American Statistical Association (ASA) and Ron_Wasserstein is the Exuctive Director of ASA. Not bad company.

Cheers.

Top 25 picks
(1) Florida 27 Tennessee 7
Texas Tech 14 (2) Texas 9
(3) USC 17 Washington 16
(4) Alabama 43 North Texas 11
(5) Penn State 38 Temple 19
(5) Mississippi 52 SE Louisiana 15
Florida State 15 (7) BYU 10
(8) Cal 32 Minnesota 22
(9) LSU 14 Louisiana-Lafayette 6
(10) Boise State 32 Fresno State 20
(11) Ohio State 48 Toledo 21
(12) Oklahoma 16 Tulsa 15
(19) Nebraska 48 (13) Virgina Tech 14
(20) Miami (FL) 69 (14) Georgia Tech 60 (This game already happened)
(15) TCU 56 Texas State 16
Rice 80 (16) Oklahoma State 33
(17) Cincinnati 84 Oregon State 33
Oregon 16 (18) Utah 12
(21) Houston BYE
(22) Kansas 29 Duke 19
Arkansas 97 (23) Georgia 12
(24) North Carolina 30 East Carolina 13
(25) Michigan 106 Eastern Michigan 33

So obviously the model has some flaws. I’m working on it.

Cheers.

Strange Maps.

Cheers.

After losing both ends of a slow pitch softball double header this past Sunday, I showed up at my friend’s (Mike) house to watch football. Dejected, I brought over the remnants of a 12 pack of Miller Light from the previous weekend. The following exchange then took place:

Mike: “Ugh. Miller Light”
Me: “It all the same. Miller Light, Bud Light, Coors Light….”
Mike: “No way. It’s easy to tell the difference.”
Me: “Oh yeah. Prove it.”

This led to a trip to the the store for red plastic cups and pizza. I brought Miller Light, and he had Bud Light in his fridge. So it was the Bud Light versus Miller Light challenge.

So we set it up. A modern day frat house version of Fisher’s lady tasting tea experiment. 8 cups. 4 Bud Light. 4 Miller Light.

Now, Mike claimed that not only could he tell that there was a difference, he could tell which beer was which without any point of reference (besides his entire life experience). This meant he claimed to be able to drink the first cup and name which beer it was without contrasting it against any other cup. Quite the claim.

Out of 8 cups, Mike figured if he got 6 correct that should prove that he can tell the difference. However, correctly identifying 6 of 8 yields a one sided p-value of 0.243. Good, but hardly statistical proof. Usually a p-value of <.05 is required. So, Mike had to go 8 for 8 to prove it to me. (A p-value of 0.0143).

Well, after some dramatics and going back and changing a guess, our hero Michael did go 8 for 8. A true connoisseur of light beer. Congratulations. (Or condolences, depending on your view).

As for me, I can't tell the difference and went 2 for 8 cause it's all the same.

Cheers.

Looks like Brian Urlacher is out for the year. I wonder how much this injury will affect the Bears (0-1), who looked terrible with Mr. Cutler as their quarterback.

If only there was a place to look up this kind of information. Some sort of network of inter-connected ideas…..

I was poking around the Freakonomics blog, and they link to an article in the New York Times by Brian Barnwell who discusses the impact of injuries on football teams. The article is here.
And the Freakonomics post is here.

Cheers.