Chapter 5 Technology HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.1: Using a TI-83/84 Plus Calculator to Calculate a Poisson Probability A popular accounting office takes in an average of 2.78 new tax returns per day during tax season. What is the probability that on a given day during tax season the firm will take in 4 new tax returns? Assume that the number of tax returns follows a Poisson distribution. Use a TI-83/84 Plus calculator to calculate this value. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.1: Using a TI-83/84 Plus Calculator to Calculate a Poisson Probability (cont.) Solution We need the value of the Poisson probability for λ = 2.78 and x = 4. Since we want the probability of exactly four successes, we will use option C:poissonpdf(. Press and then to access the DISTR menu and then scroll down to option C. Enter 2.78 for μ and 4 for x, as shown in the screenshot. Thus, P X 4 0.1544. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.1: Using a TI-83/84 Plus Calculator to Calculate a Poisson Probability (cont.) HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.2: Using Microsoft Excel to Calculate a Binomial Probability What is the probability of getting exactly six heads in ten tosses of a fair coin? Solution If we define “getting a head” as a success, then we want the probability of 6 successes. There are 10 trials and the probability of getting a success on any trial is 0.5. Since we want the probability of exactly 6 successes, we do not want the cumulative probability, so we will let cumulative be FALSE. So we would type in the following formula: = BINOM.DIST(6, 10, 0.5, FALSE). HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.2: Using Microsoft Excel to Calculate a Binomial Probability (cont.) This formula returns the value 0.205078125. Thus, the probability of getting exactly six heads in ten tosses of a fair coin is approximately 0.2051. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.3: Using Microsoft Excel to Calculate a Poisson Probability Suppose that a length of copper wiring averages one defect every 200 feet. What is the probability that a 300-foot stretch will have no defects? Solution Each defect in the wire is independent of any other defect, and the average number of defects in a given length of wire is constant. Thus, this scenario can be modeled by a Poisson distribution. Because we are looking for the probability of seeing no defects, x = 0. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.3: Using Microsoft Excel to Calculate a Poisson Probability (cont.) If there is 1 defect on average every 200 feet, then we can expect 1.5 defects for a 300-foot stretch; thus λ = 1.5. Since we want the probability of exactly 0 defects, we do not want the cumulative probability, so we will let cumulative be FALSE. Thus, we would enter the following formula: = POISSON.DIST(0, 1.5, FALSE). This formula returns the value 0.22313016. Thus, the probability that a 300-foot section of wiring will have no defects is approximately 0.2231. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.4: Using Microsoft Excel to Calculate a Hypergeometric Probability At the local grocery there are twenty boxes of cereal on one shelf, half of which contain a prize. Suppose that you buy three boxes of cereal. What is the probability that all three boxes contain a prize? Solution Each box purchased is considered a trial, so the number of trials is 3. A box with a prize is considered a success, and since we are looking for the probability that all 3 trials are successes, the number of successes obtained is also 3. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.4: Using Microsoft Excel to Calculate a Hypergeometric Probability (cont.) The population size is 20. Half of the boxes in the population are successes, so there are 10 successes in the population. Since we want the probability of exactly 3 successes, we do not want the cumulative probability, so we will let cumulative be FALSE. Thus, we enter the following formula: = HYPGEOM.DIST(3, 3, 10, 20, FALSE). This formula returns the value 0.105263158. Thus, the probability that all three boxes contain a prize is approximately 0.1053. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.5: Using MINITAB to Calculate a Cumulative Binomial Probability A local pizza place offers free large pizzas on Thursday nights. The offer is good provided that the customer correctly guesses the outcome of a coin toss when the pizza is ordered. Also, the offer can be used to receive a maximum of four free pizzas per customer. John arrives at the restaurant wanting to purchase at least three pizzas. What is the probability that he will be able to get at least three pizzas for free? Use Minitab to calculate the probability. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.5: Using MINITAB to Calculate a Cumulative Binomial Probability (cont.) Solution First, state the problem: we want to know the probability of at least 3 successful coin flips, where each trial (coin flip) has a 0.5 probability of success. The number of trials is 4 since the offer can be used for a maximum of 4 free pizzas per customer. This is the complement of the cumulative probability of 2 or fewer successes in 4 trials. Choose Calc ► Probability Distributions ► Binomial. Enter 4 for the number of trials and 0.5 for the event probability. Select Input constant and enter 2 in the box. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.5: Using MINITAB to Calculate a Cumulative Binomial Probability (cont.) Make sure Cumulative probability is selected and click OK. The Binomial Distribution dialog box is shown in the following screenshot. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.5: Using MINITAB to Calculate a Cumulative Binomial Probability (cont.) HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example T.5: Using MINITAB to Calculate a Cumulative Binomial Probability (cont.) The probability, 0.6875, is displayed in the Session window. Since this is the probability of two or fewer successful coin flips, 1 - 0.6875 = 0.3125 is the probability of getting at least three pizzas for free. HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved.