1. Discrete and Random Variables
a. Random Variables
i. Must take on a numerical value
b. Discrete Random Variables
i. Countable items. Finite number of possibilities
that have a probability assigned to them.
c. Continuous Random Variable
i. Infinite number of possibilities. Probability for
such events is done over an interval rather than
an individual number.
ii. Area under any density curve is equal to one.
The area will now become the probability.
iii. Use of the normal curve.
2. Mean and Variance of Random Variables
a. The mean for any random variable is also called the
Expected Value. In other words the average “mu” is
what is expected out of the probability distribution.
b. The variance or standard deviation squared is the
amount of variation the data contains within the
3. Rules for the Mean and Variance
i. If X is a random variable then, (see pg. 418)
ii. If X and Y are random variables then (see pg.
i. If X is a random variable then, (see pg. 420)
ii. If X and Y are random variables and X and Y are
independent of each other then, (see pg. 420)
iii. If X and Y are random variables and X and Y are
not independent of each other then, (see pg.
421) where rho is the correlation coefficient
between X and Y.