You play the role of Emma Thomson, a data analyst in the Research and Analysis Group at the Real Estate Institute of Victoria (REIV). 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 REIV is the increasing 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 over $1 million, with this trend only set to continue as evidenced from recent auction and private sales figures (refer to the documents million dollar suburbs.pdf and buyers smash records.pdf – sourced from the Melbourne’s Herald Sun). Just recently you have been working on a pilot survey from the City of Kingfisherbay concerning house prices, rental costs and returns, as well as other related data.
• Your report should be no longer than 2000 words and there is no need to include, Charts and Tables, or Appendices in the report
• Your Charts/Graphics and Tables are only to be placed in the Data Analysis file i.e. the Excel spreadsheet
• The report is to be written as a stand?alone document (assume Paul will only read your report). Thus, you should not have any references in the report to your data analysis output. Eg. “According to Table 1 in the analysis…”
• Your report must have an informative title
• Your report must contain an executive summary that explains in plain language what the report is for and summarises the main findings. The executive summary should be no more than a page
• The body of your report must be set out in the same order as in the originating memorandum from Paul Anderson, with each section (question) clearly marked
• Use plain language and your explanations succinct. Avoid the use of technical or statistical jargon as Paul Anderson will not necessarily understand statistical terms. 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 this case?
In order to prepare a reply to Paul’s memorandum, you will need to examine and analyse the dataset KingfisherbayData.xlsx thoroughly.
Paul has asked a number of questions and your Data Analysis output (i.e. your charts/tables/graphs) should be structured such that each question is answered on the separate tab/worksheet provided in your Excel document. There are also extra tabs in KingfisherbayData.xlsx called CI, SampleSize and HT and you should use the various templates contained in these tabs in your “CI_Mean/CI_Proportion”, “SampleSize” and “HT_Mean/HT_Proportion” 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 each question:
• Numerical Summary Measures (Inc. Outlier detection)
• Suitable tables and charts or graphics (Module One) that will illustrate more clearly, other important features of a variable Numerical variables can be converted to categorical variables
• Comparative Summary Measures, Scatter diagrams, Correlation analysis and Cross Tabulations (sometimes called Contingency Tables), used to establish the relationships (dependencies) between two variables
• 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 are asked to provide an estimate of a population parameter.
• We Use Hypothesis Tests when we are testing a Claim, a Theory or a Standard. Use 5% significance in any hypothesis tests you perform, and provide a summary of your conclusions. Where appropriate, make comparisons with other levels of significance (2%, 1%).
• Sample size calculation: You can assume that a 95% confidence level is appropriate. You may 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 memo.
• Marks will be lost if you use unexplained technical terms, irrelevant material, or have poor presentation/ organization
Submission Your completed assignment should be in two separate files:
• Data Analysis (Part A): An Excel document containing separate tabs/ worksheets with charts/ tables/ graphs for each question
• Report (Part B): A Word document of no more than 2000 words which is not to contain any charts/ tables/ graphs
• All interpretations should be presented in your “Report” and the excel document should only contain your intermediate analysis and final output
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