a) You are required to carry out a suitable time series analysis using the MINITAB project file SALES.MPJ.  The data set pertains to 8 years of monthly sales (£'000s) for a company.

A management accountant in the product division was asked to develop a model that could be used to obtain short-term forecasts of the monthly demand.  Comment upon your results and the methodology used.

b) You are required to carry out a regression analysis using the MINITAB project file FINANCIAL.MPJ.  The database contains financial data on 100 companies.  Use Total Revenues, Total Assets, Return on Equity, Earnings per Share, Average Yield and Dividends per Share to predict the average P/E ratio for a company.

The analysis should include any necessary diagnostic procedures to validate your results.  It should also cover the regression diagnostics to check the validity of the data and the assumptions underlying linear regression.  You are reminded that your analysis should contain adequate statistical analysis with appropriate discussions to convey your understanding of the statistical procedures involved.

Present your findings in the form of a technical report which should be word-processed. The style and presentation of your work is, however, important and should be in-line with what would be presented in a commercial/business environment

Capture electronically, the regression results from MINITAB and to import them into WORD so that they can be edited and presented in a professional manner.

Required:

1. Build a suitable time series model for forecasting the monthly spot prices and carry out a suitable forecast.

2. Build a regression model to predict the monthly returns on Microsoft stock using an appropriate selection of the given variables. 

3. Carry out any necessary diagnostic procedures in order to verify the validity of your chosen models.

3.  Interprete the various relevant MINITAB output from your various analysis.

4.  Write a technical report providing a full interpretation of your findings, a justification of your chosen models with supporting evidence, make any recommendations you think are appropriate and outline any shortcomings of the approach you have used.