Vanessa has a utility function for income given by U(I) = VI (that is the square root of income). Because of the nature of her utility function, we know that Vanessa is risk averse. Vanessa is %3D considering an investment that would give her an income of $10,000 with a probability of 0.5 or an income of $15,000 with probability of 0.5. The expected utility of this investment is (rounded to 2 decimal places): 1440 4
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- 4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob>ChiSq 0.0013* 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?The following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/ 24 hr). Predictor Coef SE Coef T P Constant 0.8489 0.4148 2.06 0.84 Weight 0.39782 0.02978 13.52 0.000 S = 0.517508 R-Sq = 96.6% (a) Write out the least-squares equation. = + x (b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.)(c) What is the value of the correlation coefficient r? (Use 3 decimal places.)The probability of a transistor failing between t = a months and t = b months is given by c ect dt. for some constant c. (a) If the probability of failure within the first six months is 10%, what is c? Round your answer to four decimal places. eTextbook and Media (b) Given the value of c in part (a), what is the probability the transistor fails within the second six months? Round your answer to the nearest integer.
- A light fixture contains five lightbulbs. The lifetime of each bulb is exponentially distributed with mean 199.0 hours. Whenever a bulb burns out, it is replaced. Let T be the time of the first bulb replacement. Let X1, i = 1, . . . , 5, be the lifetimes of the five bulbs. Assume the lifetimes of the bulbs are independent. 1. Find P( X1 > 100). (Round the final answer to four decimal places.) 2. Find P( X1 > 100 and X2 > 100 and • • • and X5 > 100). (Round the final answer to four decimal places.) 3. Find P(T ≤ 100). (Round the final answer to four decimal places.) 4. Let t be any positive number. Find P(T ≤ t), which is the cumulative distribution function of T. 5. Find the mean of T. (Round the final answer to two decimal places.)The following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/ 24 hr). Predictor Coef SE Coef T P Constant 0.8678 0.4148 2.06 0.84 Weight 0.40376 0.02978 13.52 0.000 S = 0.517508 R-Sq = 94.6% (a) Write out the least-squares equation. = + x (b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.)(c) What is the value of the correlation coefficient r? (Use 3 decimal places.) 4.You are a researcher who wants to know what the mean (µ) level of anxiety would be for the whole population if they were all receiving a new anti-anxiety therapy. You can’t give the therapy to the whole population, so you give it to a sample, and you get M = 32.1 as the average anxiety level for the sample on the therapy. What is the reason that you can’t just simply assume that µ = 32.1? You didn’t use random assignment Sampling error Descriptive statistics Inferential statistics
- 4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob> ChiSq 0.0013 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?The following Minitab display gives information regarding the relationship between the body weight of a child (in kilogramS) and the metabolic rate of the child (in 100 kcal/ 24 hr). Predictor Сoef SE Coef T P Constant 0.8489 0.4148 2.06 0.84 Weight 0.39647 0.02978 13.52 0.000 S = 0.517508 R-Sq = 97.4% (a) Write out the least-squares equation. (b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.) (c) What is the value of the correlation coefficient r? (Use 3 decimal places.)In baseball there are many ways to estimate what a team's winning percentage (w) should be against its opponents, given the total runs it has scored and the total runs it has allowed in a certain number of games. Bill James's Pythagorean Formula for the winning percentage estimator is given below. wpe = w = [(# runs scored)2]/[(# runs scored)2 + (# runs allowed)2] A team has currently scored 369 runs and allowed 329 runs. If the team does not allow any more runs for the rest of the season, how many additional runs must they score in order to have a wpe of 80%? (Hint: Let x = the number of runs additional scored.)
- The 2010 U.S. Census found the chance of a household being a certain size. The data is in the pmf below ("Households by age," 2013). Let X be the number (size) in a household. E(X) = k·P(X = k) 7 (or more) P(X=k) 0.267 0.336 0.158 0.137 0.063 0.024 0.015 k 1 2 3 5 6 a) The probability of a household size being more than 5, P(X > 5) = % b) In the long run, we are expected to see a household size of, E(X)= on average. Round answer to three decimal places. c) The probability that the size of a household is equal to two is %. d) The probability of a household size being three OR six is %.The Arrow-Pratt measures of absolute and relative risk aversion respectively describe the willingness of a consumers to risk a fixed amount of wealth or a fixed fraction of their wealth. This problem will demonstrate this by setting up a simple investment problem. Suppose that consumers begin with initial wealth Wo and may buy shares of a risky asset whose payoff per share is given by 2. (1 w/ prob. P, X = 1-1 w/ prob.1– p. Therefore buying { shares of the risky asset yields final wealth W = Wo +X. Suppose that each consumer may buy an unlimited number of shares, and seeks to maximize expected utility of final wealth max E[u(W)]. (a) Expand the consumer's expected utility maximization problem, and find the first order condition. (b) Let Cara be a consumer whose utility function exhibits constant absolute risk aver- sion UA(W) = 1– e-aW Find Cara's optimal number of shares and show that it does not depend on her starting wealth Wo-