Probability Models, Expected Values, and Bayes Formula

Question 1

The Expected Value of a random variable is

Answer 1

the Weighted Average of the Possible Outcomes for the Variable

Question 2

Variance and Standard Deviation measure

Answer 2

the Dispersion of a Random Variable around its expected value, sometimes referred to as the Volatility of a random variable

Question 3

Variance (from a probability model) can be calculated as

Answer 3

the Probability-Weighted sum of the squared deviations from the mean (or expected value).

Question 4

The Standard Deviation is the

Answer 4

Positive Square Root of the Variance

Question 5

a Probability Tree is used to show

Answer 5

the Probabilities of Various Outcomes

Question 6

Expected Values or Expected Returns can be calculated using

Answer 6

Conditional Probabilities. As the name implies, these are values contingent on the outcome of some other event.

An analyst would use a conditional expected value to revise his expectations when new information arrives

Question 7

Bayes’ Formula is to used to…. And its formula is

Answer 7

update a given set of prior probabilities for a given event in response to the arrival of new information.

(Probability of new info for a given event
___________________________________________
Unconditional probability of new info)

X

Prior probability of event