Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

Like this presentation? Why not share!

3,431 views

3,252 views

3,252 views

Published on

Mathematical Expectation And Variance

No Downloads

Total views

3,431

On SlideShare

0

From Embeds

0

Number of Embeds

130

Shares

0

Downloads

0

Comments

0

Likes

1

No embeds

No notes for slide

- 1. 1.5 Mathematical Expectation and Variance<br />
- 2. If a random variable X takes on the values x1,x2,…,xk, with the probability f(x1), f(x2), …, f(xk), its mathematical expectation or expected value is <br /> = x1· f(x1) + x2· f(x2) + … + xk· f(xk) <br />Mathematical Expectation<br />
- 3. Mathematical Expectation<br />Suppose a game has n outcomes A1, A2,…, An with corresponding probabilities p1, p2,…, pn where pi =P(Ai) and p1 + p2 + … + pn = 1. Suppose the pay off to the player on outcome Ai is ai, where a positive ai is a win for the player and a negative ai is a loss. Then expected value for the player will be<br />E = a1p1 + a2p2 + ….+ anpn<br />This quantity is called the mathematical expectation for the player.<br />
- 4. Mathematical Expectation<br />The expectation E is the amount that the player can expect to win on the average each time the game is played.<br />If E is positive then game is in the favor of the player.<br />If E is negative the game is biased against the player.<br />Suppose E = 0 then the game is said to be fair and a player’s winnings and losses should be about equal when the fair game is played a large number of times<br />
- 5. Mathematical Expectation<br />Definition: If the probabilities of obtaining the amounts a1, a2 ,…, or an are p1, p2, … and pn, then the mathematical expectation is <br />E = a1p1 + a2p2 + …+ anpn<br />Note:a’s are positive when they represent profit, winnings or gain and they are negative when they represent loss, deficits or penalties.<br />
- 6. Mathematical Expectation<br />Definition: The odds that an event will occur are given by the ratio of the probability that the event will occur to the probability that the event will not occur provided neither probability is zero. i.e. if p is the probability of the event A then odds that event will occur<br />If the odds for the occurrence of event A are a to b, where a and b are positive integers, then probability of event A is <br />
- 7. Mathematical Expectation<br />The average amount by which the values of the random variable deviate from mean is given by<br />Unfortunately,<br />
- 8. Variance of a Random Variable.<br />
- 9.
- 10. Standard deviation of a Random variable.<br />

No public clipboards found for this slide

×
### Save the most important slides with Clipping

Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.

Be the first to comment