Statistics are Like Bikinis Warming Doubters Leaning on (Multicollinearity) -

I do not like putting people in groups. However it happens.

Take this statement. People who consume Fruits such as blueberries and or Nuts tend to have live longer. Sounds reasonable, however one can never usually prove it people who consume these foods tend to do other healthy things such as exorcise and wearing seat belts.

Remember along time back when the cigarette companies used to say you can not prove cigarettes are hazardous to ones health. In a sense it was true because smokers tended to not exorcise and have a poor diet.

Then there are the Global warming Naysayers.

Monday brought climate news that can only be described as, well, frightening. An apparently-unstoppable melting process of the huge West Antarctica ice sheet has begun, which will almost certainly lead to long-feared rises in sea levels. The total rise over the next few centuries could be ten feet or more—far beyond the point that would be catastrophic for millions living in coastal areas.
Nathan Pippenger -Democracy Journal

In this case some on the right see it as attack on our economic system, much like the abolishment of slavery was many years ago. This despite the havoc weather change is causing right now In this case they are using  Multicollinearity to cloud the issue just to perpetuate the use of fossil fuels.

Even the Democracy journal tends to skim over another issue and that is Methane. We as a society consume, slaughter and consume animals at a rate that is unheard of.

 

It is the second biggest contributor to global warming. Methane occurs naturally and is the primary component of natural gas. It constitutes 1.8ppm, or 0.00018% of the atmosphere.

 

 

Which takes me back to point number one. People who consume lots og meat tend to eat less blueberries and nuts.

 

Sometimes a bikini is just a bikini.

 



Collinearity is a linear association between two explanatory variables. Two variables are perfectly collinear if there is an exact linear relationship between the two. For example, and are perfectly collinear if there exist parameters and such that, for all observations i, we have

Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related. We have perfect multicollinearity if, for example as in the equation above, the correlation between two independent variables is equal to 1 or -1. In practice, we rarely face perfect multicollinearity in a data set. More commonly, the issue of multicollinearity arises when there is an approximate linear relationship among two or more independent variables.
Mathematically, a set of variables is perfectly multicollinear if there exist one or more exact linear relationships among some of the variables. For example, we may have

Statistics are like bikinis and the Trail Blazers -Part3

Just expect the unexpected.
And sit and be amazed.

When Harden excels
and Howard
and The Rockets
are playing quite well.

On paper, statiscally the
Rockets beat the Blazers.

A team playing together
won tonight against another
team playing together.

Some times it comes down
to the unbelivable,

Wow.