In a multiplicative seasonal model, we multiply a “base” forecast by an appropriate seasonal index. These...
In a multiplicative seasonal model, we multiply a “base” forecast by an appropriate seasonal index. These seasonal components typically average to 0. True or False?
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Answer:-
In a multiplicative seasonal model, we multiply a “base” forecast by an appropriate seasonal index. These seasonal components typically average to 0.
The statement is True.
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In a multiplicative seasonal model, we multiply a “base”
forecast by an appropriate seasonal index. These...
Answer the following question true or false: The seasonal index is an indicator of forecast accuracy.
Answer the following question true or false: The seasonal index is an indicator of forecast accuracy.
Which of the following is TRUE (check all the correct choices, wrong answers will incur negative...
Which of the following is TRUE (check all the correct choices, wrong answers will incur negative marking To find MAPE, you need to find the absolute difference between the actual value and the forecast, then divide this absolute difference by the forecast value. Then take the average of all these absolute percentage errors. To find MAD, you need to find the difference between the actual value and the forecast and then take the average of all these differences To find...
5. The components of time-series are: a. Trend, Seasonal, Movement, and Random b. Trend, Mobility, Cyclical,...
5. The components of time-series are: a. Trend, Seasonal, Movement, and Random b. Trend, Mobility, Cyclical, and Seasonal c. Trend, Seasonal, Cyclical, and Random d. Trend, Seasonal, Cyclical, and Perfection The mean absolute deviation measures the accuracy of a forecast by calculating.. a. the mid-point of absolute forecasting error per period of historical data. b. the average absolute forecasting error per period of historical data. c. the standard deviation of absolute forecasting error per period of historical data d. both...
TEST, I need Help A.S.A.P PLease!!! I need to submit this within the next hour and a half. It's...
1. Regression is always a superior forecasting method to exponential smoothing, so regression should be used whenever the appropriate software is available. (Points :1)TrueFalse2. Time-series models rely on judgment in an attempt to incorporate qualitative or subjective factors into the forecasting model. (Points : 1)TrueFalse3. A trend-projection forecasting method is a causal forecasting method. (Points : 1)TrueFalse4. Qualitative models attempt to incorporate judgmental or subjective factors into the forecasting model. (Points : 1)TrueFalse5. The naive forecast for the next period...
True/False: a) If the Consumer Price Index is 125% of the base year in 2006 and...
True/False: a) If the Consumer Price Index is 125% of the base year in 2006 and 135% of the base year in 2007, the CPI increased by 10% from 2006-2007 b) When Internal Rate of Return is greater than Cost Benefit Ratio we should make the investment c) Demand curves for non-rival goods are summed vertically d) For any given good, Willingness to Accept is often larger than Willingness to Pay Please provide explanation for why its True or False
If we model a tax on the demand side, then the equilibrium price we reach will...
If we model a tax on the demand side, then the equilibrium price we reach will be higher than if we model the tax on suppliers. True False When we model a tax, the new equilibrium price represents the price paid by the buyers the revenue raised from the tax O the price the sellers keep O the amount of the tax Question 39 (1 point) Which of the following is not an appropriate way to model a tax? shifting...
A) Discuss what the time series decomposition tells you about your data series. Include discussio...
a) Discuss what the time series decomposition tells you about
your data series. Include discussion of the seasonal, cyclical, and
trend components.
b) Compare the time series decomposition forecasts with Holt
Winters. Within the sample, is the times series decomposition or
Holt Winters more accurate? Try to explain why. (see below for
data)
Audit Trail- Statistics Accuracy Measures MAPE R-Square Value 1.65% 98.99% Forecast Statistics Mean Standard Deviation Value 5.06 1.04 Method Statistics Method Selected Basic Method Decomposition type Value...
QUESTION 5 A carnival runs for 10 days a year. Attendance for each day in each of the past three years has been captured and is provided in the table below. sing the multiplicative seasonal met...
QUESTION 5 A carnival runs for 10 days a year. Attendance for each day in each of the past three years has been captured and is provided in the table below. sing the multiplicative seasonal method, determine the average seasonal index for Day 2. Year 1 Year 2 Year 3 Dayl 13,578 14,471 15,421 Day2 21,659 21,630 21,124 Day3 20,051 20,558 20,367 Day4 12,035 12,820 13,315 Day5 12,264 12,924 12,077 Day6 13,139 13,875 13,818 Day7 18,754 18,801 19,491 Day8 21,670...
A regression model with quarterly seasonal dummy variables was fit to quarterly sales data (in $10,000)...
A regression model with quarterly seasonal dummy variables was fit to quarterly sales data (in $10,000) for a small company. The results are shown below. The dummy variables are defined as follows: Q1 = 1 if the time period is Quarter 1, and otherwise. Q2 and Q3 are defined similarly. Abbreviations Used in the Output • "R-Sq" stands for "r squared" • "R-Sq" stands for "adjusted r squared • s stands for "regression standard error," equal to SSE V n-(p+1)...
Which one of the following statements is NOT true? We can use the index numbers to...
Which one of the following statements is NOT true? We can use the index numbers to determine the percentage change any year from the base year. The weighting percentage for the Paasche Index is always the percentage for the time period for which the index is being computed. The idea is that the prices in the base period should be weighted relative to their current use, not to what that use level was in other periods. You can use the...
Which of the following is TRUE (check all the correct choices, wrong answers will incur negative marking To find MAPE, you need to find the absolute difference between the actual value and the forecast, then divide this absolute difference by the forecast value. Then take the average of all these absolute percentage errors. To find MAD, you need to find the difference between the actual value and the forecast and then take the average of all these differences To find...
5. The components of time-series are: a. Trend, Seasonal, Movement, and Random b. Trend, Mobility, Cyclical, and Seasonal c. Trend, Seasonal, Cyclical, and Random d. Trend, Seasonal, Cyclical, and Perfection The mean absolute deviation measures the accuracy of a forecast by calculating.. a. the mid-point of absolute forecasting error per period of historical data. b. the average absolute forecasting error per period of historical data. c. the standard deviation of absolute forecasting error per period of historical data d. both...
If we model a tax on the demand side, then the equilibrium price we reach will be higher than if we model the tax on suppliers. True False When we model a tax, the new equilibrium price represents the price paid by the buyers the revenue raised from the tax O the price the sellers keep O the amount of the tax Question 39 (1 point) Which of the following is not an appropriate way to model a tax? shifting...
a) Discuss what the time series decomposition tells you about
your data series. Include discussion of the seasonal, cyclical, and
trend components.
b) Compare the time series decomposition forecasts with Holt
Winters. Within the sample, is the times series decomposition or
Holt Winters more accurate? Try to explain why. (see below for
data)
Audit Trail- Statistics Accuracy Measures MAPE R-Square Value 1.65% 98.99% Forecast Statistics Mean Standard Deviation Value 5.06 1.04 Method Statistics Method Selected Basic Method Decomposition type Value...
QUESTION 5 A carnival runs for 10 days a year. Attendance for each day in each of the past three years has been captured and is provided in the table below. sing the multiplicative seasonal method, determine the average seasonal index for Day 2. Year 1 Year 2 Year 3 Dayl 13,578 14,471 15,421 Day2 21,659 21,630 21,124 Day3 20,051 20,558 20,367 Day4 12,035 12,820 13,315 Day5 12,264 12,924 12,077 Day6 13,139 13,875 13,818 Day7 18,754 18,801 19,491 Day8 21,670...
A regression model with quarterly seasonal dummy variables was fit to quarterly sales data (in $10,000) for a small company. The results are shown below. The dummy variables are defined as follows: Q1 = 1 if the time period is Quarter 1, and otherwise. Q2 and Q3 are defined similarly. Abbreviations Used in the Output • "R-Sq" stands for "r squared" • "R-Sq" stands for "adjusted r squared • s stands for "regression standard error," equal to SSE V n-(p+1)...
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