AP Statistics Section 8.2: The Geometric Distribution.
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Transcript of AP Statistics Section 8.2: The Geometric Distribution.
AP Statistics
• Section 8.2: The Geometric Distribution
• Objective: To be able to understand and calculate geometric probabilities.
Ex. Russian Roulette
• Criteria for a Geoemtric Random Variable:1. Each observation can be classified as a success or failure.2. p is the probability of success and p is fixed.3. The observations are independent.4. The random variable measures the number of trials
necessary to obtain the first success. (it includes the 1st success)
If data are produced in a geometric setting and X = the number of trials until the first success occurs, then X is called a geometric random variable.
Geometrical Probability Formula:Let X be a geometric random variable and n be the number of trials until we obtain our first success. If X~G(p), then
The geometric probability distribution is as follows:1 2 3 … n …
P() … …F() … …
Points:• This is an infinite distribution.• The smallest X can be is 1.• Every geometric distribution is __________________.• The cumulative distribution is always
___________________.• Calculator notation:
For P(X = k) --- use geometpdf(p,X)For P(X k) --- use geometcdf(p,X)
• How can we show that the sum of the terms of an infinite distribution sum to 1?
Ex. Suppose you work at a blood bank and are interested in collecting type A blood. It is known that 15% of the population is type A. Let X represent the number of donors until and including the first type A donor is found. a. Does this example meet the criteria for a geometric setting?
b. Find probability that the first type A donor is the 4th donor of the day.
c. Find probability that the first type A donor is the 2nd donor of the day.
d. Find probability that the first type A donor occurs before the 4th donor of the day.
e. Find probability that the first type A donor is at least the 5th donor of the day.
f. Complete the probability distribution for the geometric random variable X for the first 6 terms.
P()
F()
If X ~ G(p), then and .
Two Methods for Solving P(X > n):1. 2.
Proof of method #2: