Scenario Probability Expected Return18%38%30%14%100%30%20%15%-8%1234An analyst creates a probabilistic scenario analysis for projecting stock market returns. The analyst's work is shown in the above table.The Interpretation of the table can be described as follows: The analyst assigns a probability of 18% to the first scenario, which projectsa stock market return of 18%. Subsequent rows can be interpreted similarly.The variance of the analyst's projections is closest to:11%-1%16%1%

Given the data as Scenario Probability Expected Return 1 18% 30% 2 38% 20% 3 30% 15% 4…

Answered: Scenario Probability Expected Return…

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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In a production process, the time (in minutes) taken (run time) for a production run and the number of items produced (run size) for 15 randomly selected orders are analyzed using Minitab statistical software. The Minitab output is as follows: Regression Analysis: Run time versus Run size Analysis of Variance Source DF Adj SS Adj MS F-Value Critical value Regression 1 8737.1 8737.1 29.35 ……… Error 13 3870.5 297.7 Total 14 12607.6 Model Summary S R-sq R-sq(adj) R-sq(pred) 17.2549 ……. 66.94% 61.32% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 148.4 11.3 13.13 0.000 Run size 0.2627 0.0485 ……. ……. 1.00 1- Write down the least square regression equation to predict the run time for run size. 2- Interpret the coefficients of the fitted model. 3- At 5% significance level, test if run size is a good…
ANOVA. Dr. Milgramm is conducting a patient satisfaction survey, rating how well her patients like her on a scale of 1-10. Her patients tend to fall into three categories: “Like a lot”, “like somewhat”, and “dislike a lot”. She believes that she might get different satisfaction scores from people in each group, but (because she's not great at numbers) she wants you to do an ANOVA to be sure. She has collected data from 12 patients (three equal groups) with the following results. Group 1) “Like a lot” Mean: 8 SS: 2 N: df: Group 2) “Like somewhat” Mean: 5 SS: 6 N: df: Group 3) “Dislike a lot” Mean: 2 SS: 4 N: df: Grand Mean: df Within-Group:__________ df Between-Groups:___________ Estimated Variance (S21) for Group 1: _______ Estimated Variance (S22) for Group 2: ___________ Estimated…
A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 13 units in the first year to 77 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 Total YearlySales 1 5 2 1 5 13 2 7 4 4 14 29 3 11 3 5 16 35 4 12 9 7 22 50 5 19 10 13 35 77 (a) Deseasonalize the data. (Round your answers to four decimal places.) Year Quarter Sales Adjusted Deseasonalized Seasonal Sales Index 1 1 5 1.3407 1 2 2 0.5998 1 3 1 0.4842 1 4 5 1.5753 2 1 7 1.3407 2 2 4 0.5998 2 3 4 0.4842 2 4 14 1.5753 3 1 11 1.3407 3 2 3 0.5998 3 3 5 0.4842 3 4 16 1.5753 4 1 12 1.3407 4 2 9 0.5998 4 3 7 0.4842 4 4 22 1.5753 5 1 19 1.3407 5 2 10 0.5998 5 3…
A survey of insurance professionals explores the use of technology in the industry. The table below contains the responses to the question that asked what technologies these professionals expected to be most used by the insurance industry in the coming year. Technology Wearable technology Blockchain technology Artificial Intelligence loT: retail insurance loT: commercial insurance Frequency D 8 7 13 28 4 30 Social media a. Compute the percentage of responses for each technology. b. What conclusions can you reach concerning expected technology usage in the insurance industry in the coming year? a. Compute the percentage of values for each response need. Technology Wearable technology Frequency Percentage (%) Blockchain technology 7 Artificial Intelligence 13 % loT: retail insurance 28 % loT: commercial insurance 4 1% P Type here to search & 6 %24 4 (CO T Y R W D
Part II. A medical clinic has collected the following data on patient category and health state of 300 patients. health state Women patient category Men Children Severe 20 30 25 Non-severe 100 75 50 One of these patients is selected at random. Let W= the patient is a woman; M = the patient is a man; C = the patient is a child; S = the patient's health state is severe; and N= the patient's health state is non-severe. 1. Find P(S n W). Are S and W mutually exclusive? Why 2. Find P(N UC).. 3. Find P(WIN). Are W and N independent? Why? (
Beagle Clothiers uses a weighted score for the evaluation and selection of its suppliers of trendy fashion garments. Each supplier is rated on a 10-point scale (10 = highest) for four different criteria: price, quality, delivery, and flexibility (to accommodate changes in quantity and timing). Because of the volatility of the business in which Beagle operates, flexibility is given twice the weight of each of the other three criteria, which are equally weighted (the sum of the four weights equals 1). The table shows the scores for three potential suppliers for the four performance criteria. Supplier A Supplier decimal place.) Criteria 1. Price 2. Quality 3. Delivery 4. Flexibility Based on the highest weighted score, which supplier should be selected? should be selected, with a total weighted score of 6 7 5 co C Rating Supplier B Supplier C 8 9 8 6 8 7 5 8 6 (Enter your response rounded to one
Pricilla Phranklin opened her clothing store, Pricilla Phashions, in Downtown Dover a little over three years ago. Pants, skirts, blouses, and shirts have fairly consistent sales, while things like shorts, sweater and outerwear are highly seasonal. On the other hand, dresses are a little harder to predict. Pricilla is hiring you to arrive at the best forecasting method for dresses. The following table contains three years of dress sales data Year 3 Year 1 Year 2 Mont Dema Dema h nd nd nd Jan 186 217 212 Feb 222 220 245 Mar 220 239 252 Apr 356 362 376 720 May 727 757 [1] Jun 367 376 404 Jul 340 341 354 Aug 293 290 324 Sep 305 296 338 Oct 600 600 618 325 318 679 708 4613 4694 Nov Dec Total 1. 2. 3. Dema 4. 5. 356 713 Using the dress data above, calculate the following 4949 Forecast year 3 using a simple 3 period moving average Forecast year 3 Calculate a forecast using the exponential smoothing method. Assume a = 0.20 (a) Using the information you have for years 1 & 2, calculate a…
Msc DEVELOPMENT FINANCE MDEF623: QUANTITATIVE METHODS IN DEVELOPMENT FINANCE Exercise One The manager of a department store is thinking about establishing a new billing system for the store’s credit customers. After a thoroughly financial analysis, she determines that the new billing system will be cost-effective only if the mean monthly account is more than $ 1700. A random sample of 500 monthly accounts is drawn, for which the sample mean is $1780. The manager knows that the accounts are approximately normally distributed with a standard deviation of $ 350. Can the manager conclude at 5% significance level that the new billing system will be cost-effective? (Take ) A monthly income investment scheme exists that promises variable monthly returns. An investor will invest in it only if he is assured of an average $180 monthly income. He has a sample of 300 months’ returns which has a mean of $190 and a standard deviation of $75. Should he or she invest in this scheme? You are…
A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 12 units in the first year to 76 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 1 2 3 4 5 4 7 11 12 18 2 4 forecast for quarter 2 forecast for quarter 3 forecast for quarter 4 3 9 10 1 4 5 7 13 5 14 16 22 35 Total Yearly Sales 12 29 35 50 76 (a) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data: x₁ = 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; and x3 = 1 if quarter 3, 0 otherwise. (Let t = 1 denote the time series value in quarter 1 of year 1; t = 2 denote the time series value in quarter 2 of year 1; ... and t = 20 denote the time series value in quarter 4 of year 5. Round…

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