• Introduce discrete random variables and demonstrate how to create a probability model
• Present how to calculate the expected value, variance and standard deviation of a discrete random variable
This packet has two videos teaching you all about discrete random variables. There is also a short powerpoint of definitions, and an example for you to do at the end.
This packet has a powerpoint of definitions, two videos, and an example for you to do yourself. Some terms that may be new are:
This powerpoint gives you the definitions of mean and standard deviation, as well as showing you how to find a missing probability in your table.
This video gives you the definition of a discrete random variable, and shows you an easy example of one.
This video shows you the formulas for mean, variance, and standard deviation for a discrete random variable. It also has an example for you to follow along with.
Consider the following probability distribution table:
As you can see, the probability for 6 is missing. Do the following:
1. Find the probability that X=6.
2. Find the probability that X is less than 5.
3. Find the mean of X.
4. Find the standard deviation of X.
1. Find the probability that X=6. This can be done by adding up all the known probabilities and subtracting them from 1.
P(X=6) = 1 - (.12+.26+.31) = 1-.69 = .31
2. Find the probability that X is less than 5. This includes the numbers 3 and 4. We see from the table that P(X=3) = .12 and P(X=4) = .26. Therefore, we just add them together.
P(X<5) = P(X=3) + P(X=4) = .12 + .26 = .38
3. Find the mean of X. This is done using our formula from the powerpoint.
E(X) = 3*.12 + 4*.26 + 5*.31 + 6*.31 = 4.81
Find the standard deviation of X. Once again, this is done using our formula on the powerpoint.
SD(X) = sqrt[(3-4.81)^2*.12 + (4-4.81)^2*.26 + (5-4.81)^2*.31 + (6-4.81)^2*.31] = sqrt(.393132+.170586+.011191+.438991) = sqrt(1.0139) = 1.0069