- #1

- 166

- 0

Also, can anyone explain the proof for Chebychev's rule?

Thanks very much.

- Thread starter Moose352
- Start date

- #1

- 166

- 0

Also, can anyone explain the proof for Chebychev's rule?

Thanks very much.

- #2

- 78

- 0

The standard deviation formula can be derived, my Maths teacher showed me. Unfortunately I am unable to derive it so I will not be much help there. The reason we divide by n-1 sometimes is to give as a most accurate or unbiased estimate for sample data. There is also proof for that, which I am also unable to do. Hope this helped.

Regards,

Daniel

- #3

- 166

- 0

Thanks repugno. It's good to know that there is a proof, but I will not be convinced until i see it.

- #4

- 78

- 0

Lol .. tried to give you some Mathematical proof, seems that I can't get the Latex code right. You're on your own now. :D

Last edited:

- #5

- 166

- 0

- #6

NateTG

Science Advisor

Homework Helper

- 2,450

- 6

For normal distributions it is possible to, for example, show that a certain fraction of the results are within a standard deviation of the peak.

- #7

- 166

- 0

- #8

selfAdjoint

Staff Emeritus

Gold Member

Dearly Missed

- 6,786

- 7

Any probability distribution that has moments has the mean as its first moment, and the variance as its second moment (essentially and with some tech fiddles). What are moments? well in one sense they are the parameters that determine the equation of the probability curve. The normal curve is distinguished because it has only those two moments; it is a two parameter curve. You tell me where the mean is and what the standard deviation is and I will give you the formula for that notmal curve and be able to draw it. Any other probability distribution that has moments at all - some don't - will be determined if you specify all of its moments, which may be an infinite number.

- #9

turin

Homework Helper

- 2,323

- 3

Wow, that sounds interesting. Is this like a Taylor expansion of a function? If the distribution has no moments, is it trivial?Originally posted by selfAdjoint

Any other probability distribution that has moments at all - some don't - will be determined if you specify all of its moments, which may be an infinite number.

- Last Post

- Replies
- 6

- Views
- 2K

- Last Post

- Replies
- 4

- Views
- 4K

- Last Post

- Replies
- 1

- Views
- 4K

- Last Post

- Replies
- 4

- Views
- 5K

- Last Post

- Replies
- 7

- Views
- 3K

- Last Post

- Replies
- 0

- Views
- 1K

- Last Post

- Replies
- 2

- Views
- 3K

- Last Post

- Replies
- 2

- Views
- 1K

- Last Post

- Replies
- 2

- Views
- 4K

- Last Post

- Replies
- 8

- Views
- 2K