The one-step forecasts for February through May with the use of exponential smoothing. Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

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Answer 1

Question

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

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January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.4. February March April May June ACTUAL FORECAST 100 85 96 103 82 66 90 MAD Forecasts 91 93 97 91 81 b. Calculate the MAD for all the forecasts, including January's. (Round your answer to 1 decimal place.)

Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 Value 17 14 15 3 (b) mean squared error MSE = % 4 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = 5 6 (d) What is the forecast for week 7? 12 16 15 (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =

The following gives the number of pints of type B blood used at Woodlawn Hospital in the past 6 weeks: Week Of Pints Used August 31 360 September 7 389 September 14 410 September 21 381 September 28 368 October 5 374 a. Forecast the demand for the week of October 12 using a 4-week moving average. [Select] b. What is the MAD? [Select] c. Use a 4-week weighted moving average, with weights of .1, .3, .6, and .8 using .8 for the most recent week. Forecast demand for the week of October 12. [Select] d. What is the MAD? [Select] e. Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 363 and a = .47 [Select] f. What is the MAD? [Select] g. Based on evaluating all three forecasting models, which forecast should be chosen? [Select]

Answer 2

Question

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

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Answer 3

Question

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

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Answer 4

Question

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Expert Solution & Answer

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Answer 5

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 6

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 7

Chapter 2.7, Problem 22P

a.

Summary Introduction

To calculate:The one-step forecasts for February through May with the use of exponential smoothing.

Introduction:Exponential smoothing of time series involves assigning datain exponentially decreasing weights fromlatest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 8

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 9

b.

Summary Introduction

To calculate:The difference in forecasts if value of α is 0.40.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 10

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 11

c.

Summary Introduction

To calculate: The MSEs for the forecasts obtained in parts ( a ) and ( b ) for February through April and to find out the more accurate forecasts for the value of α , based on the MSE.

Introduction: Exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations. Simply by putting the older data, less priority is given to the data. The newer data becomes more relevant to which more weight is assigned.

Answer 12

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Answer 13

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Answer 14

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Answer 15

Ch. 2.4 - Prob. 1P Ch. 2.4 - Prob. 2P Ch. 2.4 - Prob. 3P Ch. 2.4 - Prob. 4P Ch. 2.4 - Prob. 5P Ch. 2.4 - Prob. 6P Ch. 2.4 - Prob. 7P Ch. 2.4 - Prob. 8P Ch. 2.4 - Prob. 9P Ch. 2.6 - Prob. 10P

Solution Summary: The author explains that exponential smoothing of time series involves assigning datain exponentially decreasing weights from latest to oldest observations.

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