MBAS903: Business Analytics for Economic and Market Environments
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MBAS903: Business Analytics for Economic and Market Environments
Assessment 2 has 2 parts (A and B). Both are to be completed as individual
assessments and submitted to Turnitin as one file.
PART A (75% of total mark)
Hedonic House Price Model
You have been contracted to develop a hedonic house price model for a
leading real estate group. Use the dataset “AMESHOUSING3” to estimate your preferred model with “sale price in dollars” as your response variable. Nearly all variables are potentially available as explanatory variables so it will need a careful process of model specification and testing. The goal is to identify variables that assist the prediction of house prices.
Format: Business report for client
Executive summary – one paragraph overview of full project including summary of results - 5 marks
Introduction – set the scene and background of issue/problem (broad to specific issues) – 5 marks
Literature review – critical summary of research literature relating to models addressing similar types of problems (models used to predict house prices). Start with a very short summary of each paper, then structure your paragraphs around themes you identify (eg. variables used, methods) and discuss similarities or differences you identify in your research. Do not simply describe each article one by one – aim for at least 4 journal articles) - 15 marks Methodology – discuss the process you will follow (eg. checking for multicollinearity between x variables, variable and model options to be utilised, process of explanatory variable selection and what you are looking for in a preferred model – no results to appear in this section) – 15 marks
Body and analysis – correlation analysis, quick summary of the process and steps ultimately taken in your regression analysis then focus most of this section on presentation, discussion and interpret of the chosen model – 30 marks
Conclusions – wrap up the exercise with recommendations for client – 5 marks
PART B (25% of total mark)
Profit Forecasts
Use the dataset “PRODUCTANALYSIS” to produce forecasts of profits. Select “Order date” for your time variable and “Profit” as your dependent variable. You will need to select appropriate BY and Explanatory variables. You must compare at least three different types of models, at least one of which must be a hierarchical model (eg. naïve, auto, hierarchical, combined hierarchical).
Format: Brief Report
Executive summary - one paragraph overview of full project including summary of results - 5 marks
Methodology – discuss the process you will follow in variable and model selection, including how you will select the preferred model – 10 marks
Results – discuss the process followed in model selection. Present and interpret the results of the chosen model and conduct at least one forecast override – 10 marks
2023-04-14