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Chapter 17 Probability Models Geometric Binomial Normal.

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Presentation on theme: "Chapter 17 Probability Models Geometric Binomial Normal."— Presentation transcript:

1 Chapter 17 Probability Models Geometric Binomial Normal

2 Bernoulli trials Two possible outcomes Probability of success is constant Trials are independent

3 Requirement For Bernoulli trials, independence is a requirement. If the independence assumption is violated, you may still proceed as long as the sample is smaller than 10% of the population.

4 The Geometric Model p = probability of success q = 1 – p = probability of failure X = number of trials until the first success occurs Expected value (mean): Standard deviation:

5 Using the calculator 2 nd VARS (DISTR) geometpdf(p,x) pdf = probability density function P= probability of success X = number of the trial on which success is reached Individual outcome only

6 Using the calculator, part 2 2 nd VARS (DISTR) geometcdf(p,x) cdf = cumulative density function p = probability of success x = number of trials on or before success is reached

7 Warning! You may use the calculator functions, but the formula must still be written. The AP graders do not give credit for “calculator speak.”

8 The Binomial Model Calculating the probability of a given number of successes. Bernoulli trials n = number of trials p = probability of success q = probability of failure X = number of successes in n trials

9 Binomial probability Mean: Standard deviation:

10 Using the calculator 2 nd VARS (DISTR) binompdf(n,p,X) X = desired number of successes Use for individual outcomes

11 Using the calculator For total probability of x or fewer successes 2 nd VARS binomcdf(n,p,X)

12 The Normal Model For large numbers of trials Calculate the z-score Find the probability Success/Failure Condition

13 Do you agree with Marilyn?


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