1. Random Variables
a. Discrete Random Variables
i. Countable units. There is a finite amount of
outcomes with probability values
b. Continuous Random Variables
i. Infinite units. There is an infinite amount of
outcomes. Usually the random variable is defined
with an equation where the area under a curve is
equal to one.
2. Probability Distribution of Discrete Random Variables
a. Each outcome for the random variable must take on
a numerical value.
b. Each outcome is assigned a probability value.
c. The sum of the probability values must equal one.
3. Mean and Standard Deviation of the Discrete
a. Mean will now be represented as “mu”. This is
used because it represents what occurs in the
c. The Variance will now be represented as...
4. Binomial Probability Distribution
a. Binomial occurs when there are two outcomes.
Success vs. Failure.
b. Important characteristics for Binomial Probability.
i. Independent Events
ii. Set number of trials
iii. Two possible outcomes
iv. Probability of events don’t change.
5. Mean and Variance for Binomial Proability
Statistics and Probability