Geometric Distribution -...

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Geometric Distribution

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Geometric Distribution

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Review Binomial Distribution

Properties

The experiment consists of n repeated trials.

Each trial can result in just two possible outcomes.

The probability of success is the same on every trial.

The trials are independent.

𝑷 𝑿 = 𝒌 = 𝒏𝒌𝒑𝒌 𝟏 − 𝒑 𝒏−𝒌

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Ready for a Quiz?

Identify each experiment as Binomial or Not Binomial.

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Binomial or Not?

1. Tossing 20 coins and counting the number of heads

2. Picking 5 cards from a standard deck of cards and counting the number of hearts. (replacing and shuffle)

3. Choosing a card from a standard deck until you get a heart.

4. 87% of computer users use Chrome as their default browser. Choose 50 random computer users and ask what their default browser is.

5. 2% of the light bulbs defective. Count the number of bulbs you have to check to find a defective one.

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Set up but do not evaluate

3% of the Xboxes produced in a certain factory experiences the “Red Ring of Death.” What is the probability exactly 3 out of 20 sample is defective?

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Geometric Distribution

Suppose that an experiment meets all of the conditions of the binomial distribution EXCEPT that the number of trials in not fixed. Instead the trials continue until the first “success” is observed. This distribution is called the geometric probability distribution.

𝑥 = the number of trials until the first success is observed

𝑝 = probability of "success" on a single trial

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Geometric Setting

Each observation falls into one of just two categories, which for convenience we call “success” or “failure.”

The probability of a success, call it p, is the same for each observation

The observations are all independent.

The variable of interest is the number of trials required to obtain the first success.

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Example of a Geometric Distribution

Tossing a coin until it lands on heads.

We might ask

What is the probability that the first head occurs on the third flip?

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Calculating Geometric Distribution

If X has a geometric distribution with probability p of success and (1 − 𝑝) of failure on each observation, the possible values of X are 1, 2, 3, … If n is any one of these values, the probability that the first success occurs on the nth trial is

𝑃 𝑋 = 𝑛 = 1 − 𝑝 𝑛−1𝑝

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Geometric or Not?

For each of the following, determine if the experiment describes a geometric distribution. If the random variable is not geometric, identify a condition of the geometric setting that is not satisfied.

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Geometric or Not?

1. Flip a coin until you observe a tail

2. Draw a card from a deck, and replace. Count the number of times you draw until you observe a Jack.

3. There are 10 red and 5 blue marbles in a bag. You want to know how many marbles you have to draw, on average, in order to be sure that you have 3 red marbles.

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Set up but do not evaluate

Suppose we have data that suggest that 3% of a company’s hard disk drives are defective. You have been asked to determine the probability that the first defective hard drive is the fifth unit tested.

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Find the probability using a calculuator

Geometpdf(p,X)

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Mean and SD of Geometric Random Variable

Mean: 𝜇 =1

𝑝

Var: 𝜎2 =1−𝑝

𝑝2

SD: σ =1−𝑝

𝑝2

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Example 8.18 Arcade Game

George likes the game at the state fair where you toss a coin into a saucer. You win if the coin comes to rest in the saucer without sliding off. George has played this game many times and has determined that on average he wins 1 out of 12 times he plays. He believes that his chances of winning are the same for each toss. He has no reason to think that his tosses are not independent. Let X be the number of tosses until a win. George believes that this describes a geometric setting. Find the expected value, variance and the standard deviation.

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Answers

𝐸 𝑋 =1

𝑝=

1

12

𝑉𝑎𝑟 𝑋 =1−𝑝

𝑝2=

11 12

1 144 = 132

𝜎 = 11.5

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Arcade Game Continued

Find the probability that it takes more than 10 tosses until George wins a stuffed animal.

𝑃 𝑋 > 𝑛 = 1 − 𝑃 𝑋 ≤ 10

The probability that it takes more than n trials to see the first success is

𝑃 𝑋 > 𝑛 = 1 − 𝑝 𝑛

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NYC Rush Hour

In New York City at rush hour, the chance that an available taxi passes someone is 15%.

How many cabs can you expect to pass you for you to find an available cab?

What is the probability that more than 10 cabs pass you before you find one that is free?

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DONE!

Now, complete the Geometric Distribution Class Notes

(There are 3 problems for you to do!)