Use the data below to solve for the following:2. Naïve method3. Unweighted 3 month moving average4. Weighted Moving Average (3 months, with the following weights: 0.45, 0.35, 0.20)5. Simple Exponential Smoothing with the following parameters:Ft+1=32 and the α = .156. Time Series RegressionMonths123456789101112Firm's Actual Market share3032333428332927323328337. Which of the following forecasting method will you use?8. What are your basis in choosing for your forecasting techniques? Explain briefly.ONLY DO56

Time series are used to forecast the variable based on the time. There are four components in the…

Answered: 5. Simple Exponential Smoothing with…

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 estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 11,433.70 + 3312.68(Education) + 819.54 (Experience ) Suppose an employee with 7 years of education has been with the company for 5 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? 囲 Tables E Keypad Answer Keyboard Shortcuts
The following is a 7-month-demand-history for a certain product. Assuming that linear trend appears, develop the equation of regression line. Round values of coefficients to two decimal places. Use the equation to prepare a forecast for December 2004.
(d) If the life expectancy is increased by 3.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 84 years. Round to two decimal places.
1 - A simple exponential smoothing model has a current mean of 156.8. Assuming demand for next period is 170, update the value of the smoothing statistic. Let a = 0.1. 2- An electronics company has sold 145, 157, 124, 169,179, 201, 197, and 230 units of a certain stereo system quarterly for the past two years. Plot the data and fit an appropriate model. Forecast sales for the next two quarters.
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,815.11 +2563.46 (Education) +897.49(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer Tables Keypac Keyboard Shortcu
8. Suppose the following estimated regression equation was determined to predict salary based on years of experience. Estimated Salary = 27,017.66 +2343.69 (Years of Experience) What is the estimated salary for an employee with 26 years of experience? Answer:
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,135.60 + 2525.21( Education 7.35(Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8 years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make? Answer +1047.35 Tables Keypad Keyboard Shortcuts
Table 3 gives the market value of a luxury sedan (in dollars) xyears after its purchase. Find an exponential regression model of the form y= ab* for this data set. Estimate the purchase price of the sedan. Estimate the value of the sedan 10 years after its purchase. Round answers to the nearest dollar. TABLE 3 Value ($) 1 23,125 19,050 3 15,625 11,875 5 9,450 6 7,125 2.
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,896.07 + 2755.34 (Education) + 773.89 (Experience) Suppose two employees at the company have been working there for five years. One has a bachelor's degree (8.years of education) and one has a master's degree ( 10 years of education). How much more money would we expect the employee with a master's degree to make?
Describe three approaches to modeling seasonality in a regression forecast.
Consider the following table that gives the population of City A from Year 1 to Year 6. Complete all parts (a-k) to this question. Part 1: Fill-in the last two columns in the table. List your answers as a - j for the chart and answer the question k below. Round growth rate to the nearest ten-thousandth (4 decimal places). Population of City A, Year 1 to year 6 Year Population (P) Change ΔP{"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><mo>∆</mo><mi>P</mi></math>"} Growth Rate ΔPP{"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mrow><mo>∆</mo><mi>P</mi></mrow><mi>P</mi></mfrac></math>"} 1 315,422 N/A N/A 2 320,421 a. b. 3 321,765 c. d. 4 322,162 e. f. 5 331,165 g. h. 6 331,200 i. j. Part 2: k. Does it make sense to fit this data with an exponential model? Why or why…
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary = 10,160.10 +3147.75(Education) + 1230.34(Experience) Suppose an employee with 8 years of education has been with the company for 20 years (note that education years are the number of years after 8th grade). According to this model, what is his estimated annual salary? Answer Tables Keypad Keyboard Shortcuts

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5. Simple Exponential Smoothing with the following parameters: Ft+1=32 and the a = .15 6. Time Series Regression Months 1 2 3 4 5 6 7 8 9 10 11 12 Firm's Actual Market share 30 32 33 34 28 33 29 27 32 33 28 33