Section 4.1
1. A discrete random variable is one where the possible outcomes in a probability experiment can be counted.
2. A continuous random variable is one where the possible outcomes are uncountable
3. To calculate the mean of a probability distribution:
a)List all the possible values for the RV x
b)Calculate the probability of each outcome
c)Calculate the product of each x value and its probability
d) Add these products and this is your mean or expected value
4. To calculate the variance of a probability distribution:
a)Subtract the mean from each x value and square this difference
b)Multiply each squared deviation (Step "a" above) by the probability
c) Add this column and this is your variance
5. To calculate the standard deviation of your probability distribution, take the square root of your variance.
Section 4.2
1. A binomial experiment is a probability experiment where there are two possible outcomes, the experiment is performed a fixed number of times (n),and the number of successes is recorded (x). The probability of success is "p" and that of failure is "q."
2. The probability of x successes in n trials is found using the formula nCx*p^x*q^(n-x)...or using binomialpdf on TI-83 or 84 or using online calculator such as http://www.stat.berkeley.edu/~stark/Java/Html/ProbCalc.htm
3. The mean of a binomial distribution is n*p
4. The variance of a binomial distribution is n*p*q
5. The SD of a binomial distribution is the sq root of the variance
Section 4,2 - Part 1 (Geometric Probabilities)
1. The geometric probability calculates the probability that the first success in a binomial experiment will occur on trial x.
2. To calculate the geometric probability, use the formula p(x)=p*q^(x-1)
