- #1

- 39

- 0

You are using an out of date browser. It may not display this or other websites correctly.

You should upgrade or use an alternative browser.

You should upgrade or use an alternative browser.

- Thread starter selig5560
- Start date

- #1

- 39

- 0

- #2

chiro

Science Advisor

- 4,790

- 132

Hey selig5560.

The stuff in undergraduate is meant to be a basis for giving intuition before you move to a completely symbolic representation where the rigor is introduced.

It's the same for non-statistical math with calculus: you get some intuition first before you go to real and complex analysis.

A probability course with measure theory and analysis will have a good chance of being just as rigorous as a normal real analysis course if the course is using analysis and measure theory as the starting point for analyzing things.

Statistics though (and probability), is best understood in the context of the real world.

Statistics is an applied discipline, and this means looking at things that are real-world and have some basis in reality. Because of this, anything that has more rigor that it needs to have is often ignored due to the focus being an applied pursuit as opposed to a theoretical one.

There is a place for this analysis and I would compare it to the case of the engineer where they use the calculus results to do their job without having to worry about why it works.

The important thing though, is for the statistician (and the engineer in the above example) to understand the limitations of the result. If you are going to use it you need to understand how it holds and when it doesn't and the context in this regard.

Share:

- Replies
- 10

- Views
- 13K