Page 2 details further advice. This individual assignment is worth 30% of the overall module mark, with a word count of 1,500 +10%. You should avoid –10% because then you might run the risk of not addressing the assignment task sufficiently. The assignment must be submitted electronically via Turnitin. If the module leader suspects that the submitted assignment is not the work of its author, the submitting student may be called for a viva (oral presentation) on the topics of the assignment; or the work might be referred to academic standards as a case of misconduct. Please refer to the module handbook on Blackboard for the LOs assessed, the marking criteria, as
well as the assignment’s connection with employability’s employability agenda. Task You are a real estate analyst and are required to create an appropriate statistical model for investigating how, and why, London House prices change.
1. Select five or six independent variables (x 1, x 2, x 3, x 4, x 5, x 6 ) which will form the basis of your model. Justify the inclusion of your independent variables by engaging with academic references. The dependent variable (y) is the average London house prices. (10 marks) ◦ The justification does not have to be specifically for London independent variables. The justification can be general. 2. Obtain data sets on your chosen variables from 2000 to 2020 (or 2021 if you can get it) and input your data using the Excel Analysis ToolPak software. Present that data. (10 marks) ◦ The actual data of the independent variables would have to be specifically for London. ◦ You could try the National Statistics Office, the Financial Times, or the Mayor’s Office. 3. Run a multivariate regression on average London House prices (y) and your chosen independent variables. Produce a regression analysis using Excel’s Analysis ToolPak software—settle on at least three (x 1, x 2, x 3 ) from your original five or six. You can adopt an
iterative approach by removing some variables and replacing them with others. (30 marks) ◦ The objective here is to find the strongest regression in terms of maximizing R 2 while passing the F and the t-tests. 4. Using your regression results, compose a management report that: ◦ critically analyses the explanatory power of your chosen independent variables on average house prices ◦ provides suggestions for management decisions—what are the implications for real estates management of how London house prices change according to the independent
variables you settled on in 3? ▪ For example, you could say that, previously, decision-makers have focussed on x 5 ,
yet the regression suggests that the impact of this variable on y is rather limited. So decision-makers should focus on the impact of other independent variables. ▪ Also, on the basis of your regression in 3), you could try to predict how London house prices will develop in the near future, and why. (50 marks) Guidance your report should include an introduction and a conclusion, but NO executive Summary Abstract Charts or graphs should be in the body of the report, instead of in the appendix in-text referencing is required in the Harvard style do not simply add references to the main text; instead, you must engage with what the authors say in relation to the assignment tasks
in your reference list at the end, only list the sources that you actually used in the main text Question 4 has key words, that is, “critically analyse” and “provide suggestions”. This means that simply relaying facts and information will be insufficient. To assess the Learning Outcomes above, marks are awarded for the extent to which you
address the questions; therefore, do not simply describe “what happened”, which substantially differs from a critical discussion. Avoid personal opinions and unsubstantiated claims. Therefore, engage with what the references say in relation to the questions. This helps you to justify and substantiate. To do so, use Author (year) as part of your sentence structure alongside simply adding (Author, year) to the end of a sentence. In your answers, do not restate the assignment questions using your own words. Avoid mini literature reviews because they do not address a question; avoid lengthy introductions to an answer. • develop the ability to use software relevant to economic and business analysis and business decision-making Leaming Outcomes By the end of the module, successful students will display mastery of complex knowledge and skills, being able to: collect, manipulate and use hard data for managerial decision-making On successfully completing the module, students will be able to: L01 Recognise, understand and explain commonly used economic terms. Which ones could be combined to do L01? L02 Interpret and evaluate key economic and financial information given in the financial press. L03 Understand current problems in the economic environment. L04 Engage in informed discussion of such problems from the perspective of a manager, employee, entrepreneur and/or investor and be able to function at a higher level in a business environment. performance L05 Acknowledge, from a management perspective, the general principles behind using quantitative techniques and relevant software. Analysis and evaluation instead-problem solving and research