Sometimes doing uni work can be practical

External Since: Nov 26, 2004 Posts: 224

Some of you may recall I said I had to do a stats assignment this
semester for the master's, so I decided to do it on motogp (cos I was
planning on changing jobs and hence didn't want to use work data and
besides doing it on work stuff is boring)

So for anyone who cares(1), the model which best predicts the
championship rankings for motoGP turning out to be a straight forward
linear model (none of the fancy stuff added much of any value).

The variables considered included:
Prev Yr Championship pts
2yrs Prev Championship pts
No. of Motogp podiums
No. of junior class (125/250) podiums
No. of cylinders
Vee vs Inline
Dummy variables for:
Honda, Yamaha and Ducati
Rookie Year
Low Performing team
Non GP Championship winner (ie WSBK etc)

These whittled down in the parsimonious model to:

Final Championship Pts = 34.5707 + 0.4723(Last yrs points) + 0.1983(yr
before last's pts) + 28.0384(Dummy for rookie yr) + 57.3952 (Dummy for
Honda) -41.7039(dummy for low performer)

For those not familiar with stats a dummy(2) is a binary yes/no variable
- so if the rider is in their rookie year then it would be 1 for yes and
0 if it's not their rookie year.

Or to put it another way the best predictor of how you'll go next year
is how you went this year, but if you're on a Honda you have an
advantage (yes I know that's intuitively obvious but now we have
statistical "proof"(3)), and the interesting thing is a rookie is likely
to go better in their first year (keenness factor) although I'm thinking
that result may be a bit warped by Bayliss' bad trot in his second year
with ducati.

I'll tot up the podium finishes for this year and add to the data set
and predict the 05 outcome for laughs, it'll be interesting to see how
good the model actually turns out to be.

JL
1 I've tried to translate this into layman's terms, for those serious
maths heads out there I can send you the data and regression stats if
you want
2 I just KNOW Postman Pat or Clem are going to have a field day with
that one !
3 You PhD maths types bugger off, I know it's not a proof per se, it's
statistically significant etc etc <yawn> Smile

--
Poor fellow my country.
Australians do not care that their PM is a liar.
http://www.johnhowardlies.com/

External Since: May 09, 2004 Posts: 96

"John Littler" wrote
> Some of you may recall I said I had to do a stats assignment this
> semester for the master's, so I decided to do it on motogp (cos I was
> planning on changing jobs and hence didn't want to use work data and
> besides doing it on work stuff is boring)
>
> So for anyone who cares(1), the model which best predicts the
> championship rankings for motoGP turning out to be a straight forward
> linear model (none of the fancy stuff added much of any value).
>
> The variables considered included:
> Prev Yr Championship pts
> 2yrs Prev Championship pts
> No. of Motogp podiums
> No. of junior class (125/250) podiums
> No. of cylinders
> Vee vs Inline
> Dummy variables for:
> Honda, Yamaha and Ducati
> Rookie Year
> Low Performing team
> Non GP Championship winner (ie WSBK etc)
>
> These whittled down in the parsimonious model to:
>
> Final Championship Pts = 34.5707 + 0.4723(Last yrs points) + 0.1983(yr
> before last's pts) + 28.0384(Dummy for rookie yr) + 57.3952 (Dummy for
> Honda) -41.7039(dummy for low performer)
>
> For those not familiar with stats a dummy(2) is a binary yes/no variable
> - so if the rider is in their rookie year then it would be 1 for yes and
> 0 if it's not their rookie year.
>
> Or to put it another way the best predictor of how you'll go next year
> is how you went this year, but if you're on a Honda you have an
> advantage (yes I know that's intuitively obvious but now we have
> statistical "proof"(3)), and the interesting thing is a rookie is likely
> to go better in their first year (keenness factor) although I'm thinking
> that result may be a bit warped by Bayliss' bad trot in his second year
> with ducati.
>
> I'll tot up the podium finishes for this year and add to the data set
> and predict the 05 outcome for laughs, it'll be interesting to see how
> good the model actually turns out to be.
>
> JL
> 1 I've tried to translate this into layman's terms, for those serious
> maths heads out there I can send you the data and regression stats if
> you want
> 2 I just KNOW Postman Pat or Clem are going to have a field day with
> that one !
> 3 You PhD maths types bugger off, I know it's not a proof per se, it's
> statistically significant etc etc <yawn> Smile

> --
> Poor fellow my country.
> Australians do not care that their PM is a liar.
<font color=purple> > <a style='text-decoration: underline;' href="http://www.johnhowardlies.com/</font" target="_blank">http://www.johnhowardlies.com/</font</a>>

and people say I have too much time on my hands..

TB