Consider the following time series data. Week123456Value19141612 1815 (c) Use a = 0.2 to compute the exponential smoothing forecasts for the time series.Time SeriesValueWeekForecast119214316412518615Compute MSE. (Round your answer to two decimal places.)MSE-What is the forecast for week 7? (Round your answer to two decimal places.)(d) Compare the three-week moving average approach with the exponential smoothing approach using a = 0.2. Which appears to provide more accurate forecasts based on MSE? Explain.O The exponential smoothing using a - 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach.O The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach.O The exponential smoothing using a - 0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach.O The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach.(e) Use a smoothing constant of a - 0.4 to compute the exponential smoothing forecasts.Time SeriesValueWeekForecast11921431641251815in

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Answered: Week 1 2 3 4 5 6. Value 19 14 16 12 18…

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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A statistical program is recommended. A certain company has been an authorized dealer for C&D marine radios for the past seven years. Suppose the quarterly sales values for the seven years of historical data are as follows. Year Quarter 1 Quarter 2 Quarter 3 1 2 3 4 5 6 7 7 11 15 19 22 25 29 15 18 26 28 34 36 40 10 15 23 25 28 30 35 Quarter 4 4 radios radios radios radios 7 12 18. 21 20 27 Total Yearly Sales 36 51 76 90 105 111 131 (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 = 28 denote the time series value in quarter 4 of year 7. Round your numerical values to three decimal places.) 8 = (b) Compute the quarterly forecasts for next year. (Round…
.A new, miracle diabetes drug that diminishes major symptoms of diabetes has been approved by the FDA. Health care professionals and researchers believe that the new drug will prolong lifespan of diabetes patients. If the population is in steady state and the incidence is constant, what will the effect of this new drug be on the prevalence of diabetes in the population? Explain.
QUESTION 6 Empire Electronics manufactures its own k-cup coffee makers. The lifespan of its base model is exponentially distributed with a mean of 4 years. This retail chain has promoted a five-year warranty on this household appliance. Assume the time between manufacture and sale is negligible. What is the likelihood that the basic model k-cup coffee maker manufactured and sold by Empire Electronics would last at least three and one-half years? Express your answer rounded to the nearest whole percentage with percent symbol. i want accurate answer with proper explanation please
Tree-ring dating from archaeological excavation sites is used in conjunction with other chronologic evidence to estimate occupation dates of prehistoric Indian ruins in the southwestern United States. Suppose it is thought that a certain pueblo was occupied around 1294 A.D. (based on evidence from potsherds and stone tools). The following data give tree-ring dates (A.D.) from adjacent archaeological sites: 1189 1267 1268 1275 1275 1271 1272 1316 1317 1230 (i) Use a calculator with sample mean and standard deviation keys to find x and s. (Round your answers to one decimal place.) x = A.D. s = yr ii-What is the value of the sample test statistic? (Round your answer to three decimal places.)
Example 6.20 A series comprising five individual observations is as follows: 8, 5, 2, 6 and 7 Convert these numbers into standard scores.
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 24 12 20 11 19 24 16 (a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. What is the forecast for month 8? If required, round your answer to one decimal place. Do not round intermediate calculation. (b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place. (c) Which method appears to provide the better forecast? All Data average or Naiive
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 25 13 19 11 19 23 16 (a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. (b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place.
QUESTION Samuel is a butchery vendor at a local open market. His daily income and the number of hours worked for the first ten days after the lockdown period is shown below: Day Income (N$) Number of hours 1 800 6 2 900 8 3 600 4 4 1200 5 5 1400 9 6 2000 9 7 1400 8 8 900 6 9 1300 7 10 1400 8 REQUIRED TO; determine whether it is the data time series or cross sectional? Motivate the reason. Calculate and interpret the following descriptive measures for the random variable Income: Mean Median Mode 33rd percentile Interquartile range 3. Calculate and interpret the covariance between the random variables Income and Number of hours worked. 4. Calculate and interpret the correlation coefficient between the random…
A statistical program is recommended. A certain company has been an authorized dealer for C&D marine radios for the past seven years. Suppose the quarterly sales values for the seven years of historical data are as follows. Year Quarter 1 Quarter 2 Quarter 3 1 2 3 4 5 6 7 1 2 3 4 1 2 Year Quarter Sales 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 7 4 10 1 15 20 23 25 (a) Deseasonalize the data. (Round your answers to three decimal places.) 28 7 15 10 4 10 18 15 7 15 26 23 12 20 28 25 18 23 34 28 21 25 36 30 20 15 28 18 26 28 34 36 40 Adjusted Seasonal Index 0.924 1.353 1.108 0.616 0.924 1.353 1.108 0.616 0.924 1.353 1.108 0.616 0.924 1.353 1.108 0.616 0.924 1.353 1.108 0.616 0.924 1.353 1.108 0.616 10 0.924 15 23 25 28 30 35 Quarter 4 Deseasonalized Sales 6.076 X 13.867 x 4 ] D J 1 7 12 18 21 20 27 Total Yearly Sales 36 50 76 91 106 111 130
From the following series of cyclical fluctuations find the 3-yearly, 5-yearly, 7-yearly and 9-yearly moving averages. Also give your comments thereon. Year : 1989 | 1990 | 1991 | 1992 | 1993 | 1994 1995 | 1996 | 1997 | 1998 Fluctuations: 1 2 -1 -2 1 -1 -2
This cumulative review problem uses material from Chapters 3, 5, and 10. Recall that the Poisson distribution deals with rare events. Death from the kick of a horse is a rare event, even in the Prussian army. The following data are a classic example of a Poisson application to rare events. The data represent the number of deaths from the kick of a horse per army corps per year for 10 Prussian army corps over a period of time. Let x represent the number of deaths and f the frequency of x deaths. x 0 1 2 3 or more f 111 61 24 4 (a) First, we fit the data to a Poisson distribution.The Poission distribution states P(x) = e−λλx x! , where λ ≈ x (sample mean of x values). From our study of weighted averages, we get the following. x = Σxf Σf Verify that x = 0.605. Hint: For the category 3 or more, use 3. x = (b) Now we have P(x) = e−0.605(0.605)x x! for x = 0, 1, 2, 3 . Find P(0), P(1), P(2), and P(3 ≤ x). Round to three places…
The following time-series diagram tracks the performance of two stocks during the month of October. Describe the overall trend of the two stocks. By what percentage did the value of each stock increase or decrease during the month of October? Stock 2 $200 Stock 1 T$150 Stock 2 -$100 Stock 1 T$ 50 1 5 11 16 21 26 31 October a. Stock 2 increased by 200%. Stock 1 decreased by 50%. b. Stock 2 increased by 100%. Stock 1 decreased by 50% c. Stock 2 increased by 200%. Stock 1 decreased by 33% d. Stock 2 increased by 100%. Stock 1 decreased by 33%.

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Week 1 2 3 4 5 6. Value 19 14 16 12 18 15