b. What is the proportion of months in which demand is completely satisfied?c. Use the simulation model to compare the profitability of monthly replenishment levels of 140and 160 pairs of goggles. Use a 95% confidence interval on the difference between theaverage profit that each replenishment level generates to make your comparison. 1. Virtual Reality Goggle Inventory. Galaxy Co. sells virtual reality (VR) goggles, particularlytargeting customers who like to play video games. Galaxy procures each pair of goggles for $150from its supplier and sells each pair of goggles for $300. Monthly demand for the VR goggles is anormal random variable with a mean of 160 units and a standard deviation of 40 units. At thebeginning of each month, Galaxy orders enough goggles from its supplier to bring the inventorylevel up to 140 goggles. If the monthly demand is less than 140, Galaxy pays $20 per pair of gogglesthat remains in inventory at the end of the month. If the monthly demand exceeds 140, Galaxy sellsonly the 140 pairs of goggles in stock. Galaxy assigns a shortage cost of $40 for each unit of demandthat is unsatisfied to represent a loss-of-goodwill among its customers. Management would like touse a simulation model to analyze this situation.a. What is the average monthly profit resulting from its policy of stocking 140 pairs of goggles atthe beginning of each month?b. What is the proportion of months in which demand is completely satisfied?

Galaxy co. procures router at the rate of $150 and Sale the same at $300. The net profit for one…

Answered: b. What is the proportion of months in…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…
We have measurements from eight companies for the % workforce change in 2010 from 2009 and the % change in profits from 2010 to 2011. % workforce change (x): 1.0 % profit change (y): 1.5 -0.4 -2.6 -3.8 -5.8 -2.5 -0.1 0.4 0.4 0.1 -0.2 -0.5 -7.5 0.2 0.3 We can calculate: Er = -12.7, Ex² = 64.51, Συ--6.8 , Σ 57, Σεy- 46.35. Find the sample correlation between the two variables, and fit a simple linear model to the dataset. Also, plot the residuals, ri, against xi, and comment on the fit of the model.
Two new variables, the market value of the firm (a measure of firm size, in millions of dollars) and stock return (a measure of firm performance, in percentage points), are added to the regression: In(Earnings) = 3.86 – 0.28Female + 0.37In(MarketValue) + 0.004Return, (0.03) (0.04) (0.004) (0.003) n = 46,670, R = 0.345. If MarketValue increases by 1.88%, what is the increase in earnings? If MarketValue increases by 1.88%, earnings increase by 0.70 % (Round your response to two decimal places.) The coefficient on Female is now – 0.28. Why has it changed from the first regression? O A. Female is correlated with the two new included variables. O B. MarketValue is important for explaining In(Earnings). O C. The first regression suffered from omitted variable bias. OD. All of the above. Assume that the coefficient estimated in the second regression is correct. Forget about the effect of the Return variable, whose effect seems small and statistically insignificant. Calculate the correlation…
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 88 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−0.813+0.177?,h^=−0.813+0.177w, with standard error for the coefficient of ?w equal to 0.448. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
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Suppose your firm generated $50.0million$⁢50.0⁢million in sales. What would be the 95%95% prediction interval for your firm's net income? Write your answer using interval notation. Round your answer to 1 decimal place.
As a sales analyst for the shoe retailer Foot Locker, one of your responsibilities is measuring store productivity and then reporting your conclusion back to management. Foot Locker uses sales per square foot as a measure of store productivity. While preparing your report for the second quarter results (Q2), you are able to determine that annual sales for last year ran at a rate of $406 per square foot. Therefore, $406 per square foot will be your sales estimate for the population of all Foot Locker stores during Q2. For your Q2 Sales Report, you decide to take a random sample of 64 stores. Using annual data from last year, you are able to determine that the standard deviation for sales per square foot for all 3,400 stores was $80. Therefore $80 per square foot will be your population standard deviation when compiling your Q2 report. Management has asked for the probability that your sample mean based on 64 stores is 1) within $15 and 2) within $5 of the population mean…
Kenneth is studying the relationship between the time spent exercising per day and the time spent outside per day. Data were collected ranging from 20 minutes to 90 minutes per day exercising. The line of best fit for the data is given below. Assume the line of best fit is significant and there is a strong linear relationship between the variables. y= 0.13x + 40.5 Answer the following (each is equally weighted): 1. Identify the explanatory and response variables (make sure your answer is related to the application and not just in terms of x and y). 2. According to the line of best fit, what would be the predicted number of minutes spent outside for someone who spent 70 minutes exercising? 3. Would it be appropriate to use this model to predict the number of minutes spent outside for someone who spent 0 minutes exercising? Why or why not (remember to include appropriate terminology).
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 85 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−4.273+0.834?,h^=−4.273+0.834w, with standard error for the coefficient of ?w equal to 0.242. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…
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Find and interpret a 95% confidence interval for how the average weight changes for a one hour increase in sleep per night. Find and interpret a 95% confidence interval for the average weight given 6.5 hours of sleep per night is obtained.

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