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BUS 201 Project Report

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Bus 201 Project Report

BUS 201 Project Report Worth 30 Marks

Due: 11pm 7/10/2021

PART A worth 15 Marks

Look at the tube under week 6 entitled “Tube doing a multiple linear regression using Excel Add-in “.

Do a multiple regression on the “employee retention” spreadsheet.

You will need to copy to a separate spreadsheet and format, so numbers are clearly visible and correctly formatted.

Note: You may use XLMINER also; applying the same method.

  • Make Years PLE as the dependent variable and assess independent variable at 95% confidence and confirm for each variable they are explanatory in terms of dependent variable. The independent variables are: YrsEducation, College GPA, Age, Gender, College Grad and Local.

Note some of the independent variables are categories you need to translate to a numeric scale.

It is important that show the working within the separate spreadsheet i.e. ANOVA analysis testing Hypothesis of Influence at 95% confidence level,you use may use t-stat and p-stats also.

You are required to postulate hypothesis at 95% confidence level.

Formulate the multiple regression formula correctly and provide relevant statistics. Explain what the statistics mean.

PART B worth 15 Marks

Review Supplementary Chapter A on Non-linear Optimisation it is available on Moodleand provide a summary (10 marks)

and do Q9below (5 marks)

Q9

The Economic Order Quantity (EOQ) model is based on ordering only a single item. Suppose we allow for multiple items that are independent except for a budget restriction. Develop a model to minimize the total cost and meet a budget constraint on the total inventory value, defined by the product of the unit cost multiplied by the order quantity, summed over all items. Apply your model to the following data by implementing it on a spreadsheet and solving the model with Solver. Interpret the sensitivity report. Refer to Supplementary Chapter A it has data for Q9.

You are required to type in a spreadsheet and use solver add-in in Excel (You can also use XL Miner in google sheets).

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