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- September 13, 2020
- By menge

You have been asked to analyze a set of time series data to determine which forecasting method provides the best fit. The data is from a small manufacturing operation and show pounds of a particular raw material used. The manager is tracking the total amount of raw materials used per week to use in planning for upcoming orders.

Week |
Pounds Used |

1 |
603 |

2 |
584 |

3 |
563 |

4 |
579 |

5 |
581 |

6 |
552 |

·Construct an Excel workbook to analyze this data. **This file must be created from a blank template. Do Not Modify An Existing File.** If you created an Excel file during this exam to use with earlier problems, put this problem on a separate spreadsheet tab WITHIN the same file.

·Create forecasts of the data using the following method:

Linear Trend model. Use 400 as the Y axis intercept and -5 as the slope parameter. Use Solver to optimize the Mean Square Error (MSE). __Answer all the questions below from the optimized model__.

1.Calculate the Mean Absolute Deviation (MAD) and Mean Square Error (MSE). Your answers should be calculated to three (3) decimal places

2.What is the Forecast for Week 7? What are the values of the model parameters? Your answers should be calculated to three (3) decimal places.

3.Using Mean Square Error (MSE) as the criteria, if another method (Method 2) produced an MSE value of 504.385, which forecasting method (Linear Trend or Method 2) best fits this particular set of data? __Explain your reasoning__.

4.Type your answers to #1, #2, and #3

Trend Analysis

610 600 590 580 570

Actual values

Trend line Value

560 550 540 530 520 1 2 3 4

T ime 5 6 Problem Title

Forecasting Linear trend analysis Input Data

Period

Period 1

Period 2

Period 3…