To calculate MAD and MAPE for management’s technique. Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

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Answer 1

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Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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Sales of quilt covers at Bud Banis' department store in Carbondale over the past year are shown below. Management prepared a forecast using a combination of exponential smoothing and its collective judgment for the 4 months (March, April, May, and June): a) Compute MAD and MAPE for management's technique.b) Do management's results outperform (i.e., have smaller MAD and MAPE than) a naive forecast?c) Which forecast do you recommend, based on lower forecast error?

Sales of quilt covers at Bud Banis's discount department store in Carbondale over the past year are shown below. Management prepared a forecast using a combination of exponential smoothing and its collective judgment for the 4 months (March, April, May, and June): b) Using the Naive Method the forecast for period March through June is (round your response to two decimal places): Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.

The number of fishing rods selling each day is given below. Perform analyses of the time series to determine which model should be used for forecasting. 3 day moving average analysis 4 day moving average analysis 3 day weighted moving average analysis with weights W1=0.2, W2=0.3 and W3=0.5 with W1 on the oldest data. Exponential smoothing analysis with A=0.3 Which model provides a better fit of the data? Forecast day 13 sales of fishing rods using the model chosen in part (e) Day Rods Sold 1 60 2 70 3 110 4 80 5 70 6 85 7 115 8 105 9 65 10 75 11 95 12 85 Please read the relevant article, found in the VLE, before answering the question. Discuss the process and findings of the study of the article. Suggest a possible study that could be done at your current or past job that could use a similar methodology and analysis.

Answer 2

Question

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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Answer 3

Question

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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Answer 4

Question

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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Answer 5

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

Answer 6

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

Answer 7

Chapter 4, Problem 23P

a)

Summary Introduction

To determine: To calculate MAD and MAPE for management’s technique.

Introduction: A sequence of data points in successive order is known as time series. Time series forecasting is the prediction based on past events, which are at uniform time interval. Moving average method and trend projections are two of the time series methods, which use weights to prioritize past data.

Answer 8

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

Answer 9

b)

Summary Introduction

To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

Answer 10

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

Answer 11

c)

Summary Introduction

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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 how to calculate MAD and MAPE for management's technique. The absolute error for March is the modulus of the difference between 101 and 120.

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To determine: To determine whether the management’s results outperform naïve forecast by comparing MAD and MAPE.

To determine: To compare the results of management forecast and naïve forecast and to recommend a forecasting technique based on lower forecast error.

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