Wednesday, October 24, 2012

Significant Other

What’s significant in your life?

Regular person: my partner, my job, my friends, etc.

Scientist: hopefully my data

In everyday use, significance means that something is important and meaningful.

For scientists, significance has a very specific definition, which is referred to as statistical significance (http://en.wikipedia.org/wiki/Statistical_significance).

Basically, if I have a result, what are the odds my result occurred from some specific factor versus the odds that my result just occurred by chance. If I'm confident my result came from some effect, then the result is considered significant.

Sunday, October 14, 2012

I like free stuff!

Imagine your favorite ice cream shoppe gives away all of their ice cream for free!
They even include the ice cream recipes and their favorite sundae recipes.

But wait, there’s more!
Anyone can add in their favorite sundae recipes or make their own ice cream.

Sound awesome? Yes.

Well guess what, the free  ice cream sundae of software is open source software (tasty analogy, eh?).

Tuesday, October 9, 2012

So you want to be an indentured servant?

Question: How do I become an indentured servant in this day and age?

Answer: Become a postdoctoral researcher! (post-doc, http://en.wikipedia.org/wiki/Postdoctoral_research)
See also: National Postdoctoral Association (http://www.nationalpostdoc.org/policy/what-is-a-postdoc)

Why do postdocs exist?

 Graduate schools started graduating more PhDs than there were professor positions available. (Note: this is true for the sciences, but not necessarily for other disciplines.)

Monday, October 1, 2012

Proportionality and Disproportionality: Not just words with too many syllables!

This dog’s legs are disproportionately short for his body!

A proportion relates two different objects via size or some other characteristic.

To evaluate a proportion, establish three factors:
1)      The original object/group
2)      The object/group of comparison
3)      The underlying cause/relationship (if any)

Proportions go awry when someone tries to draw an incorrect conclusion from the data.