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Problem 8 a. Suppose that four different exponential smoothing methods were applied to a certain time series {y}. Based on the results shown below, what type of time series could {y} be? (Circle the correct answer) MAPE MAD MSD Single 12.23 70.18 6599.57 Exponential Smoothing Methods Double (Holt's Trend Corrected) 10.21 56.76 4883.93 Holt-Winters Additive 4.74 25.28 1007.58 Holt-Winters Multiplicative 3.855 21.222 832.898 i. A time series that has a linear trend and a constant seasonal variation. ii. A time series that has a linear trend and an increasing seasonal variation. iii. A time series that has a linear trend, but doesn't have a seasonal variation. iv. A time series that has neither a linear trend nor a seasonal variation. v. Cannot determine. b. When we apply the simple exponential smoothing method, we average the time series values to calculate the initial level estimate. True or False? (Circle the correct answer.) c. The Holt-Winters method was applied to quarterly sales data, and the initial seasonal factors for quarters 2, 3, and 4 are: sn-2 = 109, sn-₁ = 73, sno = -41. The initial seasonal factor estimate for quarter 1 (sn-3) is d. Suppose that you applied the double exponential smoothing method with a = 0.1 and y = 0.4 to the monthly demand data of a certain product by using 20 months of data. If the point estimate of y22 is 550 and s = 25, construct a 95% prediction interval for y22. Write the interval in the form: a + bc√d, i.e., write the quantities for a, b, c, and d. Do not calculate the lower and upper bounds of the interval. e. Suppose that the true relationship between y and t is given by the nonlinear model: y₁ = ßßes. A natural log transformation was applied so that a simple linear regression solution can be found. If the estimated percentage increase from y₁, to y, is 18%, what is , ?

Problem 8 a. Suppose that four different exponential smoothing methods were applied to a certain time series {y}. Based on the results shown below, what type of time series could {y} be? (Circle the correct answer) MAPE MAD MSD Single 12.23 70.18 6599.57 Exponential Smoothing Methods Double (Holt's Trend Corrected) 10.21 56.76 4883.93 Holt-Winters Additive 4.74 25.28 1007.58 Holt-Winters Multiplicative 3.855 21.222 832.898 i. A time series that has a linear trend and a constant seasonal variation. ii. A time series that has a linear trend and an increasing seasonal variation. iii. A time series that has a linear trend, but doesn't have a seasonal variation. iv. A time series that has neither a linear trend nor a seasonal variation. v. Cannot determine. b. When we apply the simple exponential smoothing method, we average the time series values to calculate the initial level estimate. True or False? (Circle the correct answer.) c. The Holt-Winters method was applied to quarterly sales data, and the initial seasonal factors for quarters 2, 3, and 4 are: sn-2 = 109, sn-₁ = 73, sno = -41. The initial seasonal factor estimate for quarter 1 (sn-3) is d. Suppose that you applied the double exponential smoothing method with a = 0.1 and y = 0.4 to the monthly demand data of a certain product by using 20 months of data. If the point estimate of y22 is 550 and s = 25, construct a 95% prediction interval for y22. Write the interval in the form: a + bc√d, i.e., write the quantities for a, b, c, and d. Do not calculate the lower and upper bounds of the interval. e. Suppose that the true relationship between y and t is given by the nonlinear model: y₁ = ßßes. A natural log transformation was applied so that a simple linear regression solution can be found. If the estimated percentage increase from y₁, to y, is 18%, what is , ?

MATLAB: An Introduction with Applications
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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Problem 8 a. Suppose that four different exponential smoothing methods were applied to a certain time series {y}. Based on the results shown below, what type of time series could {y} be? (Circle the correct answer) MAPE MAD MSD Single 12.23 70.18 6599.57 Exponential Smoothing Methods Double (Holt's Trend Corrected) 10.21 56.76 4883.93 Holt-Winters Additive 4.74 25.28 1007.58 Holt-Winters Multiplicative 3.855 21.222 832.898 i. A time series that has a linear trend and a constant seasonal variation. ii. A time series that has a linear trend and an increasing seasonal variation. iii. A time series that has a linear trend, but doesn't have a seasonal variation. iv. A time series that has neither a linear trend nor a seasonal variation. v. Cannot determine. b. When we apply the simple exponential smoothing method, we average the time series values to calculate the initial level estimate. True or False? (Circle the correct answer.) c. The Holt-Winters method was applied to quarterly sales data, and the initial seasonal factors for quarters 2, 3, and 4 are: sn-2 = 109, sn-1 = 73, sno= -41. The initial seasonal factor estimate for quarter 1 (sn-3) is d. Suppose that you applied the double exponential smoothing method with a = 0.1 and y=0.4 to the monthly demand data of a certain product by using 20 months of data. If the point estimate of y22 is 550 and s = 25, construct a 95% prediction interval for y22. Write the interval in the form: a + bc √d, i.e., write the quantities for a, b, c, and d. Do not calculate the lower and upper bounds of the interval. e. Suppose that the true relationship between y and t is given by the nonlinear model: y₁ = ßß es. A natural log transformation was applied so that a simple linear regression solution can be found. If the estimated percentage increase from y₁ to y, is 18%, what is , ?
Transcribed Image Text:Problem 8 a. Suppose that four different exponential smoothing methods were applied to a certain time series {y}. Based on the results shown below, what type of time series could {y} be? (Circle the correct answer) MAPE MAD MSD Single 12.23 70.18 6599.57 Exponential Smoothing Methods Double (Holt's Trend Corrected) 10.21 56.76 4883.93 Holt-Winters Additive 4.74 25.28 1007.58 Holt-Winters Multiplicative 3.855 21.222 832.898 i. A time series that has a linear trend and a constant seasonal variation. ii. A time series that has a linear trend and an increasing seasonal variation. iii. A time series that has a linear trend, but doesn't have a seasonal variation. iv. A time series that has neither a linear trend nor a seasonal variation. v. Cannot determine. b. When we apply the simple exponential smoothing method, we average the time series values to calculate the initial level estimate. True or False? (Circle the correct answer.) c. The Holt-Winters method was applied to quarterly sales data, and the initial seasonal factors for quarters 2, 3, and 4 are: sn-2 = 109, sn-1 = 73, sno= -41. The initial seasonal factor estimate for quarter 1 (sn-3) is d. Suppose that you applied the double exponential smoothing method with a = 0.1 and y=0.4 to the monthly demand data of a certain product by using 20 months of data. If the point estimate of y22 is 550 and s = 25, construct a 95% prediction interval for y22. Write the interval in the form: a + bc √d, i.e., write the quantities for a, b, c, and d. Do not calculate the lower and upper bounds of the interval. e. Suppose that the true relationship between y and t is given by the nonlinear model: y₁ = ßß es. A natural log transformation was applied so that a simple linear regression solution can be found. If the estimated percentage increase from y₁ to y, is 18%, what is , ?
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