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Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 17 Probability Models.

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Presentation on theme: "Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 17 Probability Models."— Presentation transcript:

1 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 17 Probability Models

2 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Bernoulli Trials The basis for the probability models we will examine in this chapter is the __________________. We have Bernoulli trials if: there are _____ possible outcomes (___________ and ____________). the probability of success, p, is ____________. the trials are ______________.

3 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Geometric Model A single Bernoulli trial is usually not all that interesting. A Geometric probability model tells us the probability for a random variable that counts the number of Bernoulli trials until the __________________. Geometric models are completely specified by one parameter, _______________________, and are denoted Geom(__).

4 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Geometric Model (cont.) Geometric probability model for Bernoulli trials: Geom(p) p = probability of success q = 1 – p = probability of failure X = # of trials until the first success occurs P(X = x) =

5 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Independence One of the important requirements for Bernoulli trials is that the trials be _________________. When we dont have an infinite population, the trials are __________________. But, there is a rule that allows us to pretend we have _________________ trials: The ___% condition: Bernoulli trials must be independent. If that assumption is violated, it is still okay to proceed as long as the sample is smaller than ____% of the population.

6 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide TI Tips Under Distributions you will find both geometpdf and geometcdf Use geometpdf(p,x) to find the probability of any ________ outcome. p is the individual probability of success and x is the number of trials until you get a success. Ex. geometpdf(.2,5) Use geometcdf(p, x) to find the probability of success ________________ the x th trial. Ex. Geometcdf(.2, 4)

7 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Ex. Approximately 3.6% of all (untreated) Jonathan apples had bitter pit in a study conducted by the botanists Ratkowsky and Martin (Australian Journal of Agricultural Research, Vol. 23, pp ). Bitter pit is a disease of apples resulting in a soggy core, which can be caused either by over watering the apple tree or by a calcium deficiency in the soil. Let n be a random variable that represents the first Jonathan apple chosen at random that has bitter pit. a) Find the probability that n = 3, n = 5, n= 12. b) Find the probability that n < 5. c) Find the probability that n > 5. d) State the mean and standard deviation.

8 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Assignment P. 398 #7-12

9 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 17 Probability Models (2)

10 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Binomial Model A Binomial model tells us the probability for a random variable that counts the number of ____________ in a fixed number of __________ _________. Two parameters define the Binomial model: ___, ___________________; and, ___, __________ _______________. We denote this Binom(n, p).

11 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Binomial Model (cont.) In n trials, there are ways to have k successes. Read n C k as ______________. Note: n! = n x (n-1) x … x 2 x 1, and n! is read as________________. (Can also be shown as) Find the following. a)b) 10 C 4

12 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Binomial Model (cont.) Binomial probability model for Bernoulli trials: Binom(n,p) n = p = q = = X = P(X = x) =

13 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley TI tips Under Distributions you will find both binompdf and binomcdf Use binompdf(n,p,x) to find the probability of any ________ outcome. n is the number of trials, p is the individual probability of success and x is the number of successes. Ex. binompdf(5,.2,2) Use binomcdf(n,p, x) to find the probability of getting _____________________successes in n trials. Ex. binomcdf(5,.2, 2) Slide

14 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Ex. A basketball player makes 70% of his freethrows. Assuming the shots are independent, what is the probability of each of the following? a)He makes exactly 3 out of the next 5 attempts. b)He makes at most 3 out of the next 5. c)He makes at least 3 out of the next 10. Slide

15 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide The Normal Model to the Rescue As long as the ________________ Condition holds, we can use the Normal model to approximate Binomial probabilities. Success/failure condition: A Binomial model is approximately Normal if we expect at least ___ successes and ____ failures:

16 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Continuous Random Variables When we use the Normal model to approximate the Binomial model, we are using a ___________ random variable to approximate a __________ random variable. So, when we use the Normal model, we no longer calculate the probability that the random variable equals a ___________ value, but only that it lies _____________ two values.

17 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Ex. An orchard owner knows that hell have to use about 6% of the apples he harvests for cider because they will have bruises or blemishes. He expects a tree to produce about 300 apples. a)Verify that you can use the normal model to approximate the distribution. b)Find the probability there will be no more than a dozen cider apples. c)Is it likely there will be more than 50 cider apples? Explain. Slide

18 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide What Can Go Wrong? Be sure you have Bernoulli trials. You need ____ outcomes per trial, a constant _________________, and _______________. Remember that the ______________ provides a reasonable substitute for _______________. Dont confuse ___________and _____________ models. Dont use the Normal approximation with ___________. You need at least ___ successes and ____ failures to use the Normal approximation.

19 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide What have we learned? Geometric model When were interested in the number of Bernoulli trials __________________________. Binomial model When were interested in the number of _________ in a certain number of Bernoulli trials. Normal model To ______________ a Binomial model when we expect at least ___ successes and ___ failures.

20 Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide Assignment P. 399 #13-15, 17, 19-21, 26, 29


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