Question:
The management of Madeira Computing is considering the introduction of a wearable electronic device with the functionality of a laptop computer and phone. The fixed cost to launch this new product is $300,000. The variable cost for the product is expected to be between $166 and $246, with a most likely value of $206 per unit. The product will sell for $300 per unit. Demand for the product is expected to range from 0 to approximately 20,000 units, with 4,000 units the most likely.
Model the variable cost as a uniform random variable with a minimum of $166 and a maximum of $246. Model the product demand as 1,000 times the value of a gamma random variable with an alpha parameter of 3 and a beta parameter of 2. Construct a simulation model to estimate the average profit and the probability that the project will result in a loss. (Use at least 1,000 trials.)
a. Develop a what-if spreadsheet model computing profit (in $) for this product in the base-case, worst-case, and best-case scenarios.
b. What is the average profit (in $)? (Round your answer to the nearest thousand.)
c. What is the probability the project will result in a loss? (Round your answer to three decimal places.)
1. IWhich of the following is a true statement for a regression analysis? II regression analysis is applied only to non-linear model II regression analysis is applied only to a multiplicative model II regression analysis is applied only to a linear model -- replical: n. regression analysis is applied only to an exponential model. l Wh it h ofthe following is not one of the four corn ponenls of experimental design? -- Determine whether the following value is a continuous random variable, discrete random variable, or not a random variable, a. The height of a randomly selected person b. The "yes" or "no" response to a survey question c. The number of pigeons in a country d. The number of statistics students now doing their homework e. The distance a football travels in the air after being thrown f. The exact time it takes to evaluate 67 + 29 a. Is the height of a randomly selected person a discrete random variable, continuous random variable, or not a random variable? O A. It is a continuous random variable B. It is a discrete random variable. O C. It is not a random variable b. Is the "yes" or "no" response to a survey question a discrete random variable, continuous random variable, or not a random variable? O A. It is a continuous random variable O B. It is a discrete random variable. O C. It is not a random variable. C. Is the number of pigeons in a country a discrete random variable, continuous randorn variable, or not a random variable? O A. It is a continuous random variable. O B. It is a discrete random variable O C. It is not a random variable. d. Is the number of statistics students now doing their homework a discrete random variable, continuous random variable, or not a random variable? O A. It is a continuous random variable O B. It is a discrete random variable, O C. It is not a random variable. @. Is the distance a football travels in the air after being thrown a discrete random variable, continuous random variable, or not a random variable ? O A. It is a discrete random variable O B. It is a continuous random variable(1 mark each) For each of the given matrices, select all decompositions that can be applied to it. You do not have to show your work for this question. 2 ) A = [61 O Diagonalization (i.e., A = PDP-1 with D diagonal) O Schur triangularization O Spectral decomposition O Singular value decomposition b ) B = 0 1.001 Diagonalization O Schur triangularization O Spectral decomposition Singular value decomposition c) C is the 75 x 75 matrix with every entry equal to 1. Diagonalization Schur triangularization O Spectral decomposition Singular value decomposition d) D = 0 1 1 Diagonalization OSchur triangularization Spectral decomposition Singular value decompositionLet X a normal random variable with mean / and variance of . Consider Z = X - H Then Z isa O normal random variable standard normal random variable O geometric random variable O uniform continuous random variable O Bernoulli random variable O Binomial random variable O exponential random variable
