Matlab, Fourth Edition: A Practical Introduction to Programming and Problem Solving
4th Edition
ISBN: 9780128045251
Author: Stormy Attaway Ph.D. Boston University
Publisher: Elsevier Science
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Chapter 6, Problem 14E
To determine
To find:
The modification in the program of Exercise 13 so that the
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Chapter 6 Solutions
Matlab, Fourth Edition: A Practical Introduction to Programming and Problem Solving
Ch. 6 - Prob. 6.1PCh. 6 - Prob. 6.2PCh. 6 - Prob. 6.3PCh. 6 - Prob. 6.4PCh. 6 - Prob. 6.5PCh. 6 - Prob. 6.6PCh. 6 - Prob. 6.7PCh. 6 - Prob. 1ECh. 6 - Prob. 2ECh. 6 - Prob. 3E
Ch. 6 - Prob. 4ECh. 6 - Prob. 5ECh. 6 - Prob. 6ECh. 6 - Prob. 7ECh. 6 - Prob. 8ECh. 6 - Prob. 9ECh. 6 - Prob. 10ECh. 6 - Prob. 11ECh. 6 - Prob. 12ECh. 6 - Prob. 13ECh. 6 - Prob. 14ECh. 6 - Prob. 15ECh. 6 - Prob. 16ECh. 6 - Prob. 17ECh. 6 - Prob. 18ECh. 6 - Prob. 19ECh. 6 - Prob. 20ECh. 6 - Prob. 21ECh. 6 - Prob. 22ECh. 6 - Prob. 23ECh. 6 - Prob. 24ECh. 6 - Prob. 25ECh. 6 - Prob. 26ECh. 6 - Prob. 27ECh. 6 - Prob. 28ECh. 6 - Prob. 29E
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- Suppose that the number of expensive goods X sold in a shop over 24 days, is Poisson random variable with rate 240, i.e. X Poisson (240), where > 0 is the expected number of sales per day and is the unknown parameter that we would like to estimate. Suppose further that can take three possible values 0₁ = 1/2, 0, 1/4 and 0₁ = 1/8, with prior probabilities 0.2, 0.5 and 0.3, respectively. Suppose now that we observe that x=10 expensive goods were sold in the last 24 days. (a) Write down the likelihood function for and find the MLE of 0. (b) Given the observed data 2 = 10, what is the posterior distribution of 0, p(0 | x= 10)? (c) What is the posterior mean for ? (d) What is the posterior standard deviation for 0? [Hint: You may use the fact if X is a random variable, then var(X) = E(X²) – [E(X)]²].arrow_forwardA machine is built to make mass-produced items. Each item made by the machine has a probability of being defective. Given the value of 0, the items are independent of each other, where is unknown and would like to estimate. Suppose has for prior distribution a Beta(a, ß) distribution, where a > 0 and 3>0. The machine is tested by producing items until the first defective occurs. Suppose that the first 12 items are not defective but the y = 13th item is defective. (a) Write down the likelihood function for 0 and find the MLE of 0. (b) Given the observed data y = 13, what is the posterior distribution of 0, p(0 | y = 13)? Take a = 1 and ẞ= 19. (c) What are the parameters of the posterior distribution? (d) What is the posterior mean for 0? (e) What is the posterior standard deviation? =arrow_forwardSuppose that the number of expensive goods X sold in a shop over 24 days, is Poisson random variable with rate 240, i.e. X Poisson (240), where > 0 is the expected number of sales per day and is the unknown parameter that we would like to estimate. Suppose further that can take three possible values 0₁ = 1/2, 0, 1/4 and 0₁ = 1/8, with prior probabilities 0.2, 0.5 and 0.3, respectively. Suppose now that we observe that x=10 expensive goods were sold in the last 24 days. (a) Write down the likelihood function for and find the MLE of 0. (b) Given the observed data 2 = 10, what is the posterior distribution of 0, p(0 | x= 10)? (c) What is the posterior mean for ? (d) What is the posterior standard deviation for 0? [Hint: You may use the fact if X is a random variable, then var(X) = E(X²) – [E(X)]²].arrow_forward
- 4. Suppose you are investigating the properties of three random variables called "A", "B", and "C", and you discover the following information about them: A ~ N(0,1); B ~ C~X(μc, 2), where all observations on "A" are independent, and, "B" and "C" are independent of each other. Use this information to answer the following questions. (a.) Suppose we create a new variable, "D", as: What type of distribution does "D" have? D = (b.) What are the degrees of freedom of "D" in this example? (c.) Suppose we create a new variable, "E", as: 45 E == ΣΑ i=1 What type of distribution does "E" have? (d.) What are the degrees of freedom of "E" in this example?arrow_forward23. If P(A)=0.4, P(A or B)=0.9, and P(A and B)=0.2. find P(B). A. 0.7° B. 0.3 C. -0.7 D. 0.5arrow_forward6 In Statistics class, the probability that a randomly-selected student was born in India is 0.07. 10 students are independently and randomly selected. What is the probability that at least one of them was born in India? 9 a) 0.07 b) 0.93 c) 0.48 d) 0.52arrow_forward
- Normal DistributionHeights of students are normally distributed with mean 170 cm and standard deviation 6 cm.Find the probability that a student’s height is between 164 cm and 176 cm.arrow_forwardBinomial DistributionA coin is tossed 6 times.Find the probability of getting exactly 4 heads.arrow_forwardThe average number of calls received by a call center in 10 minutes is 3.Find the probability that exactly 5 calls are received in 10 minutes.arrow_forward
- A population has mean 50 and standard deviation 10.If a random sample of size 25 is taken, find the standard error of the mean.arrow_forwardA manufacturer claims that the mean life of their bulbs is 1200 hours with a standard deviation of 100 hours.A sample of 25 bulbs has a mean life of 1170 hours.Test the claim at a 5% significance level.arrow_forwardFor the matrix A below, find a nonzero vector in Nul A and a nonzero vector in Col A. 4 2 -4 0 A= - 12 -4 20 -8 12 2-28 16 Find a nonzero vector in Nul A.arrow_forward
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