How to boil an egg - statistics to the rescue

Even for experienced cooks boiling an egg can be a difficult task. How can you achieve the perfect result with a runny yoke but firm white when you can’t see inside the shell? With all the other kinds of cooked eggs, fried, poached, scrambled, even omelettes, you can see how cooked the egg is and stop when it is how you like it. With boiled eggs you must rely on timing.

Large or extra-large eggs will take longer to cook than those classified as small or medium. You might, for example, typically cook a large egg in a pan of boiling salted water for seven minutes. Even if you do this and apply exactly the same amount of heat to the pan the results will not always be the same. Sometimes you will find the egg harder than you like it while on other occasions it will be too soft. The reason for this is straightforward: there can be quite a bit of variation in size and weight within a category such as ”large”.

For example the pack of nine eggs that I bought from the local co-op yesterday contained eggs varying in weight from 66 grams to 74 grams, with a mean between 69 and 70 grams and a standard deviation of about 2.5 grams. (Even these figures are not entirely accurate as my kitchen weighing machine only registers the nearest whole number of grams.)

Suppose you find that an egg weighing 70 grams was exactly as you like it when cooked for 7 minutes. This means that you should allow 1 minute for every 10 grams. In accordance with this you will get improved results if you weigh each egg before cooking and adjust the time in the pan appropriately. So a 65 gram egg should be cooked for six and a half minutes while a 75 gram egg would need seven and a half minutes. Timings for other weight eggs should be suitably adjusted. This approach should give you a perfect boiled egg every time!

Granger

There really is no danger
That we'll forget Clive Granger
Nobel prize winner that he became
Cointegrated series brought him to fame
More care in studying trends
Was what he taught us
And gave the concept to his name
From Nottingham to UCSD
With Robert Engle by his side
For econometricians everywhere
He is a source of pride.

Backing Bayes

According to Thomas Bayes
Everything is conditional
And of probability he says
We should not be traditional
When new information comes
You must redo all your sums
With prior and posterior
This approach is superior
Must more realistic
To give you a statistic.

Econometrics Journal special session online

Webcasts of some of the keynote lectures at the 2013 Royal Economic Society conference, held at Royal Holloway University of London, are now available online.

This includes an Econometrics Journal special session on Heterogeneity, chaired by Richard Smith of Cambridge University.

Multicollinearity madness

My independent variables are highly correlated
And coefficient standard errors consequently are inflated
The estimates' significance are downright understated
These results are making me totally frustrated

The R squared is high
But the t stats are all low
The reason for this we all know
It's multicollinearity madness
I've got multicollinearity madness

I guess I'll just have to wait 'til later
See if I can get a bit more data

Factor analysis is not my style
And ridge regressions are not worthwhile
There are no restrictions that I can use
Or regressors in the model that I could lose

The VIF is far too high
The tolerance is far to low
The reason for this we all know
It's multicollinearity madness
I've got multicollinearity madness

I guess I'll just have to wait 'til later
See if I can get a bit more data

XtransX to the minus one X transpose Y

X trans X to the minus one

X transpose Y

I said X trans X to the minus one

X transpose Y

you know that beta hat

is calculated like that

they call it OLS

when you want to regress

it's a fitting tool

that will give to you

the lowest RSS

yes that's the OLS

X trans X to the minus one

X transpose Y

I said X trans X to the minus one

X transpose Y

you know that beta hat

is calculated like that

Ordinary but rather neat

For ease of use it just can't be beat

A simple formula

and the calculation's complete

And you will find it BLUE

when all the assumptions are true

X trans X to the minus one

X transpose Y

I said X trans X to the minus one

X transpose Y

you know that beta hat

is calculated like that

they call it OLS

when you want to regress

it's a fitting tool

that will give to you

the lowest RSS

yes that's the OLS

Keep to the beta - more punometrics

In this subject make sure
That you don't lose the plot
It will give you some clues,
Likely as not
Make sure you're aware
Of what causes what
For modelling it well
Surely matters a lot.

There are many symbols around
Alphas, gammas and betas
Deltas and rhos, and pi's, chi's and thetas
Upper and lower, two cases of sigma
To sum up it's hard, a right old enigma.

You've got hats, you've got bars
And one or two stars
You've got F's, you've got t's
And hypotheses
Reject or accept
You will need to decide
Both tails to be used
Or only one side?

You need to regress
So you can progress
Good results will impress
And give you success

So keep to the beta
It will make your life sweeter
For nothing is better
Than this famous Greek letter.

Hal White RIP

I am feeling particularly sad today as I heard this morning that Hal White, Professor Halbert White Jr of UCSD, passed away last Saturday morning.  James Hamilton has written a brief appreciation about him  here.

I had the privilege of meeting Hal at the Clive Granger Memorial Conference back in May 2010. I can only concur with what others have said and written about him - he was both an extremely good econometrician and a very friendly and delightful man.

I shall be singing Heteroskedasticity Blues in memory of him later today.