Lec7 Discrete Random Variables, and Probability

Lec7 Discrete Random Variables, and Probability

1. Random Variable

   • a variable which can take on different values (or outcomes), with each value (or outcome) having an associated probability.

2. Discrete vs Continuous Random Variables

   • :  “X” can only take on certain     values.  Examples:

3. Probability Distributions for a Discrete Random Variable X

   • is a table of the possible values of the random variable, and their accompanying probabilities.  (Looks like a table of relative frequencies)
   • (Looks like a table of relative frequencies)

4. Mean, Variance, and Standard Deviation for Discrete Probability Distributions

   • Mean
     • weighted average” approach for the mean of a probability distribution because the variable can take on different values = “the expected value”.
       • Excel’s SumProduct function
   • The Variance:
     • do not use the Excel function for “Variance” when dealing with a probability distribution
   • The Standard Deviation:
   • SumProduct
     • find the result of two columns of numbers multiplied together, and then the totalled

Images and files in the map