The forecast for the first 7 days and select the forecast with the best absolute deviation. Introduction: Exponential smoothing: In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

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Answer 1

Question

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

c)

Summary Introduction

To explain: What does the example illustrate.

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The following are the sales figures for 2018 through 2020 for a product. Data for ayear is available in two halves of the year, months January through June, and thenJuly through December (Half-year 2). Suppose we are interested in setting up a forecasting model using the exponentialsmoothing method for stationary processes with seasonality.a) Initialize the system based on the data provided for 2018 and 2019.b) Suppose the smoothing factors are ?= 0.1 and ?= 0.1. Forecast and update forthe first half of 2020 and then the second half of 2020 by incorporating the sales forthe first half of 2020 . Calculate the MAD based on 2020actuals and forecasts.c) Forecast sales for the two halves of 2021.

Elna inc is a microwave manufacturing and distribution company based in Jakarta. The company needs to estimate production demand using the historical sales data of the last 24 months (periods).A logistics manager of the company then uses the moving average, exponential smoothing, and simple linear regression methods to determine sales forecasts for the next 12 months (Graphically illustrate the results). Provide an analysis and the results of bias, MAPE, MSE, and MAD for the forecasting decisions.Moving average is 4 month, and alfa is 0.05

MONTH DEMAND 1 45 2 3 4 5 48 43 48 49 6 54 7 8 9 10 47 50 46 47 Using the table above, calculate two forecasts using the following method:-i. First, for periods 4 through 10, develop the exponentially smoothed forecastsusing a forecast for period 3 (F3) of 45.0 and an alpha of 0.4. ii. Calculate the weighted moving average for periods 4 through 10, using weights of.70, .20, and .10, with 0.70 applied to the most recent data iii. Calculate the mean absolute deviation (MAD) for each forecasting procedure.Which forecasting procedure would you select? Why?

Answer 2

Question

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

c)

Summary Introduction

To explain: What does the example illustrate.

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Answer 3

Question

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

c)

Summary Introduction

To explain: What does the example illustrate.

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Answer 4

Question

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

c)

Summary Introduction

To explain: What does the example illustrate.

Expert Solution & Answer

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Answer 5

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

c)

Summary Introduction

To explain: What does the example illustrate.

Answer 6

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

Answer 7

Chapter 10, Problem 14P

a)

Summary Introduction

To prepare: The forecast for the first 7 days and select the forecast with the best absolute deviation.

Introduction:

Exponential smoothing:

In the exponential smoothing forecast method, older data is given lesser importance and the newer data is given more importance. It is efficient for making short term forecasts.

Answer 8

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

Answer 9

b)

Summary Introduction

To prepare: The forecast for the last 7 days and compare the total absolute deviation.

Answer 10

c)

Summary Introduction

To explain: What does the example illustrate.

Answer 11

c)

Summary Introduction

To explain: What does the example illustrate.

Answer 12

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Answer 13

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Answer 14

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Answer 15

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Solution Summary: The author explains the exponential smoothing forecast method, which gives older data less importance and newer data more importance. The spreadsheet model using 3-period moving average provides the better results.

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To prepare: The forecast for the last 7 days and compare the total absolute deviation.

To explain: What does the example illustrate.

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Chapter 10 Solutions