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Apply quantitative methods within the decision-making process.
Analyse and examine quantitative methods used in the business environment.
Demonstrate and apply the principles and methods of research.
Utilise common statistical tools contained within standard business software
(particularly spreadsheets).
Background Information
This is an exercise in exploratory data analysis.
Your research firm, Numbers ‘R’ Us, has been hired by Property2Go, a New Zealand real estate company with offices throughout the country. The New Zealand real estate market is usually stable but over the last three months there has been a small reduction in the number of properties being listed and sold. The management of Property2Go is concerned that this indicates growth prospects for the industry are weak for the foreseeable future. Therefore to increase productivity Property2Go either needs to capture more market share or reduce its costs.
To reduce costs Property2Go is restructuring their business and planning to dismiss 5% of their current real estate sales staff. In order to avoid being accused of unfairly dismissing any real estate sales staff member they want to base the dismissal process on the sales data of the real estate agents. Property2Go would also like to be able to identify a benchmark sales figure for their remaining real estate agents so they can assess their performance against other firms in the New Zealand real estate market, but they currently do not have suitable data.
The file: A1 Data.xlsx has been supplied by Propert2Go. It contains sales data from the last three months for all their real estate salespeople. You should take a few minutes to familiarize yourself with this file and see what data is included.
1. Data Manipulation
When inspecting the data you notice that total value of sales is included, but not the average sales price for each salesperson. Use the data provided to calculate the average sales price.
You also notice that age of the real estate agents is provided as a continuous variable, when it is common in research for age data to be collected as a discrete variable. Construct a new age variable using the following age groups: 20-29, 30-39, 40-49, 50-59.
For each age group calculate mean, median, mode, and standard deviation for both the number of sales and average sales price. Report the results in a table.
2. Descriptive statistics and correlations
Your next task is to calculate a range of suitable statistics to look for indications that sales performance is in any way related to the age or gender of the real estate agents; as this has been requested by the client.
For the client provide a written summary of your findings supported by appropriate tables and/or graphs. This should report the important points from the data and explain the implications of your findings for Property2Go.
3. Benchmarking
Property2Go managers want to benchmark their firm against others in the real estate industry but do not have suitable data. Your final task is to undertake an online search to identify free, publically available sources of New Zealand real estate data.
For one (1) data source you believe provides good benchmarking data provide a description of the data available, paying particular attention to similarities and differences between the data you find online and the data provided by Property2Go.
4 Principles of Research
Discuss whether you believe any of the research activities your consultancy firm has been asked to perform by Property2Go raise ethical issues.
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