E1.4. Expectation and Variance of a Random Variable (Econometrics Math)

This video defines expectation and variance of a random variable and gives an example of how to compute expectation and variance.

Throughout the video, I also demonstrate important results in the application of probability to econometrics: (1) expectations are linear, (2) expectations of an indicator function, (3) variance of a linear function, and (4) computational formula for the variance.

This video is part of my series of videos on an introduction to econometrics. This is part of the math review.

Category:

Education

Tags:

• expectation
• mean
• random variable
• variance
• linear function
• mean of a linear function
• variance of a linear function
• linear formulas
• econometrics
• probability
• statistics
• math

[pedersande]

Do you have a video on conditional expectations? BTW thank you so much for this resource it is very helpful!

[intromediateecon]

@pedersande Thanks for the comment. I allude to how to compute conditional expectations when I give the video on the law of iterated expectations (E1.7), but I don't formally define conditional expectation on its own. Here's what I would recommend:

Watch the video on joint, marginal and conditional distributions (to learn what a conditional distn is).

Watch the iterated expectations video. Basically, once you have a conditional pdf or pmf, you use that in place of the marginal pdf/pmf.

[Koni804]

is 0>P(A)<1  part of the forumla

[CHRISM1011]

The skips are very distracting. Can you just post the whole video? Nonetheless, Thank You Very much for this.

[sethshich]

Thanks! Great explanation!

[sethshich]

great explanation!!! Thanks!

[thebestfella]

you are awesome, thanks aloooooooot