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业务预测和模拟论文

时间:2015-09-06 10:57来源:www.ukassignment.org 作者:yaapoo 点击:
BSS009-3 Business Forecasting and Simulation
Assignment One – Forecasting (weighted 50%)
 
 
This is an individual assignment.
这种分配将被提交为两部分。第一部分的60%和第二部分的40%加权。第一部分是一份书面报告,第二个是实用的元素,都包括使用Excel的预测任务。
This assignment will be submitted into two parts.  The first part will be weighted 40% whilst the second part will be weighted 60%.  The first part is a written report and the second a practical element, which will comprise a forecasting task using Excel.
 
The data for the assignment and instructions on how to download it are available via the unit BREO site.
 
Part One  -  Written Report
 
Write a report (maximum 2,000 words) explaining, with appropriate referenced theory, the methodology that you intend to use in order to produce a four-step ahead forecast for your dataset.  The report should cover the following areas:-
1. An examination of the data and description of the nature of the dataset with which you have been supplied. (40%)
2. Discussion and justification of the three techniques you have decided to use; (30%)
3. Your reasons for rejecting other techniques that you consider inappropriate; (20%)
4. Some discussion of other forecasting issues that should be considered when attempting to produce medium to long term forecasts (10%)
 
Note:-     Your report must include a printout of the Excel graph of your data.
Make sure that you submit a Microsoft Word 2003 file.
 
Part Two  -   Practical Excel assignment
 
Using the data supplied, carry out the tasks detailed below and submit a single Excel file with your spreadsheet work as required by the instructions for each task.  Where comments are required these should be included on the sheets.
 
Task 1 (5%)   
Graph the data – remembering everything which should be included on a good chart or graph.
 
Task 2 (80%)
使用三种不同的和适当的预测模型数据集的预测技术。
使用三种措施的拟合优度(误差测试),测试模型。
绘制拟合模型(预测)和原始数据,在同一个图表和注释适合你的模型。
从每个模型的残差的性质和评论绘制残差(错误)。
Using three different and appropriate forecasting techniques, produce forecasting models for the data set. 
Test the models using three measures of goodness of fit (error tests).
 
Plot the fitted models (your forecasts) and the original data on the same chart and comment on the goodness of fit of your models.
Plot the residuals (errors) from each model and comment on the nature of the residuals.
 
Task 3 (15%)
Produce a forecast for the next four periods using the most accurate of your models.
 
As well as the tasks above, you will be assessed on your presentation and use of Excel.
 
NOTE – Although you may include in your file the models that you have tried but rejected after testing, as well as the model which is your final choice, the rejected models may not be considered when marking.  You may only ask for assistance in respect of the operation of the spreadsheet, not in the choice of technique.
 
Submission Dates:
Part One – Written Report: 10.00 a.m. Monday 26th November 2012
Part Two – Practical Excel models: 10.00 a.m. Monday 14th January 2013
 
Both parts must be submitted through BREO.
 
Note: You will see from the schedule that time has been set aside in Weeks 8 and 11 for working on the assignment.  In addition, there will be plenty of opportunities to ask for help during class times.  I will be happy to provide appropriate support to students www.ukassignment.org who have made a reasonable attempt.  Please don’t leave the work till the last minute; I may not be available (in person or via e-mail) over the Christmas break.
 
Return Dates: I will aim to provide feedback (including the grade) through BREO by the following dates:
 
Part One:  Monday 17th December 2012.
Part Two: Monday 4th February 2013.
 
You will receive feedback through Turnitin on BREO.  If you require further, more detailed feedback, then please speak to me.
 
 
Learning Outcomes covered in this assignment:
1 Select appropriate forecasting approaches in a range of commonly occurring business situations. Select and justify a forecasting approach relevant to the given problem by examining the strengths and weaknesses of different models.
2 Prepare and evaluate data for use in forecasting applications. Analyse data for both regular patterns and abnormal behaviour and make appropriate selections of, and adjustments to, the data for detailed analysis.
3 Participate in a range of forecasting activities using comport-based models where appropriate and report on the results Work either individually or as part of a group to build forecasting model, produce a written report explaining the techniques used and the results obtained and commenting on any operational and implementation issues which must be borne in mind.
4 Evaluate the performance of forecasts using appropriate techniques Carry out statistical analysis of errors.
 
 


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