MIS770 Foundation Skills in Data Analysis Assignment

Context/Scenario

You play the role of Daniel Williams, a data analysist at the Beachside Real Estate agency in the City of Beach-side, a council located in Melbourne, Victoria. Your role includes analyzing a variety of housing data including house prices, affordability, investment returns, rental availability and rental returns. You are often required to report outcomes of your analysis to senior managers at the Institute who have little or no knowledge of data analysis. Of specific interest to the Beachside Real Estate agency is the decreasing house prices in Melbourne and potentially what this will mean for buyers yet to enter the market. A recent analysis, which received publicity in the media, showed that there were more Melbourne suburbs with a median house price of under $1 million, with this trend only set to continue as evidenced from recent auction and private sales figures.

Just recently, you have been working on a pilot survey data from the City of Beachside concerning house prices, rental costs and returns, as well as other related data. In light of the above, the Beachside Real Estate agency is very interested to see where the City of Beachside, and more specifically its suburbs, is/are positioned when it comes to house prices and affordability. Zoe Stewart, the Director of the Beachside Real Estate agency, has written to you regarding the Beachside housing survey. Her memo to you is reproduced in next page.

Specific Requirements

Before attempting the assignment, make sure you have prepared yourself well. At a minimum, please read the relevant sections of the prescribed textbook and review the materials provided in Modules 1 and 2.

Report Requirements

• Your report must have a cover sheet containing your personal particulars and the Unit details, an executive summary, introduction and conclusion.
• Your report should be no longer than 4 pages excluding cover sheet, and there is no need to, any visualisations (i.e., Charts and Tables), or Appendices in the Report.
• The Charts/Graphics and Tables you create are only to be placed in the Data Analysis file (i.e. the Excel spreadsheet) and not reproduced in the report.
• Your report is meant to be a stand-alone document. That is, it should be able to be read without looking at the data analysis. To this end, do not refer to the visualisations as “as you can see from Figure 1 etc”. You need to interpret your data analysis visualisations for Zoe in the report.
• Suggested Word formatting for the report: Single-line spacing; no smaller that 10- point font; page margins approx. 25mm, and good use of white space.
• Set out the report in the same order as in the originating Memorandum from Zoe, with each section (question) clearly marked.
• Use plain language and keep your explanations succinct. Avoid the use of technical or statistical jargon. As a guide to the meaning of “Plain Language”, imagine you are explaining your findings to a person without any statistical training (e.g., someone who has not studied this unit). What type of language would you use in that case?
• Marks will be lost if you use unexplained technical terms, irrelevant material, or have poor presentation/organisation.
• All Microsoft Excel output associated with each question in the Memorandum is to be placed in the corresponding tab in the file BeachsidePropertySurvey_yourstudentid.xlsx

Data Analysis Instructions/Guidelines

In order to prepare a reply to Zoe’s memorandum, you will need to examine and analyse the dataset BeachsidePropertySurvey.xlsx thoroughly.

Zoe has asked a number of questions and your data analysis output (i.e., your charts/tables/graphs) should be structured such that you answer each question on the separate tab/worksheet provided in your Excel document. There are also three extra tabs in BeachsidePropertySurvey.xlsx called CI, HT and SS and you should use the various templates contained in these tabs in your “Confidence Interval”, “Hypothesis” and “Sample Size” answers.

In order to effectively answer the questions, your data analysis output needs to be appropriate. Accordingly, you’ll need to establish which of the following techniques are applicable for any given question:

• Summary Measures (e.g., descriptive statistics, Inc. outlier detection, percentiles).
• Comparative Summary Measures (i.e., descriptive statistics, outlier detection and percentiles for multiple values of a variable).
• Suitable tables (such as a frequency distribution) and charts or graphics (such as histograms, box plots, pie charts, bar/column charts, polygons) that will illustrate more clearly, other important features of a variable.
• Scatter Diagrams (used to visually establish if there is a relationship between two numeric variables).
• Cross Tabulations (sometimes called contingency tables), used to establish the relationships (dependencies) between two variables (see Additional Materials under Topic 2 – Creating Cross Tabulations in Excel using Pivot Tables).
• Confidence Intervals. You can assume that a 95% confidence level is appropriate. We use confidence intervals when we have no idea about the population parameter we are investigating. Additionally, we would use confidence intervals if we were asked for an estimate. You should use the relevant Excel templates provided in the dataset and copy them to the applicable question tab.
• Hypothesis Tests. You can assume that a 5% level of significance is appropriate. We use hypothesis tests when we are testing a claim, a theory or a standard. You should use the relevant Excel templates provided in the dataset and copy them to the applicable question tab.
• Sample size calculation: You can assume that a 95% confidence level is appropriate. You should include comparisons for 90% and 99% and a recommendation for the appropriate sample size.
• To answer some questions, you may need to make certain assumptions about the data set we are using. Mention these in your data analysis, where relevant. There is no need to mention this in the report.

Note: There is an appendix at the end of each chapter of the prescribed textbook which describes the basic Excel steps associated with that topic. Chapters 1 to 9 are applicable for this assessment.