# Variance of Poker

- Strategy videos

(9 Votes)
8954
## Description

In this video you will learn about variance and how to measure it, how common downswings are and how to adjust your bankroll accordingly, and how to cope with the mental challenges variance poses to you.

## Comments (18)

newest first#1

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#4

thanks for the vid

#5

R statistical software: http://www.r-project.org/

#6

Material like this is often a challenge, but learning it is doable and important to managing your poker career. If there's anything that's unclear, I'd be happy to answer any questions.

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#9

What your asking for here is an analitical solution to these questions. There used to be an app on another site that attempted to answer the probablity of an XBB downswing question. I would have included it, but it was removed.

So baring that, you would have to work from first principles and derive the solution. Essentially you'd be looking for the distribution of the minimum of the sum of a finite number of independent, identically distributed normal random variables. A couple of years ago when I was in grad school, I attempted to derive the solution to this problem. After a while, I decided simulation was the easier course.

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#12

PS: I have recognized the unbiased estimator of the variance, studies memories^^

#13

a little more focus on "what does this mean" would help most players imo. When you're looking at SD, calculating the deviations from the mean, and then squaring them I think many players would want to hear you explicitly mention that "we're juts doing this to get rid of the negative values because otherwise the sum of all deviations is zero"... and that "to look at the extent of the dispersion we need an absolute value of the difference from our expected outcome"...

or something like this.

#14

I don't think it will fit here. I'd be happy to email it over. My email is leader2p2 (at) gmail /dot/ com.

Pira0,

My two years of spanish in high school is unfortunately insufficient to this material :(

QnS1086,

This is for LHE? Also sample standard deviation isn't an unbiased estimator of true standard deviation as the square root is not a uniform function though it is asymptotically unbiased iirc.

Datsmahname,

The problem with that explanation is that it's also a fly by on the truth. For example, we could use mean absolute deviation or range or dozens of other statistics to measure dispersion, but we use variance because of it's relationship to the central limit theorem. The reason the formula is the way it is isn't for the reasons you state. It's because when you derive an unbiased estimator for the second centered moment and then take the square root, that's what you get.

So imo the only way to properly explain it would be to show the derivation. That would confusing and useless to most so I just tell people the truth. This is the formula. Here's how you use it. If you want to know why it is what it is, you can go to grad school or pick up a stat theory book. If not, just trust me, and we'll move on to the next thing.

#15

And where can I find a code listing of your programme?TFA

#16

What do you think about "Poker Variance Simulator" (available on rival webstie)

#17

when you say 10% 425bb is variance , why downswing?

i SHOULD have 10% possibility to be 425bb up , in my bankroll, right?

#18

he does talk about variance working both ways at about 2:30.

the reason people concentrate on negative variance & downswings is simply the risk of ruin.