ECON940: Statistics for Decision Making - Economics Assignment Help

Assignment Task:

An Australian real estate investment trust that owns and operates income-producing residential real estate in Sydney area is now keen to expand its presence in Sydney CBD and also create a further diversified property portfolio. The company has collected data for 190 potential investment properties on Sydney market (the data is on an excel file named “REALESTATE”). Assume you work for this company as an Analyst and have been asked to do a preliminary study of the real estate market. You can now use this data to study the main characteristics of these potential investment properties so the company will be in a better position to decide about investing in new property types and achieving its strategic objectives. You were given specific instructions to carry out descriptive and prescriptive analytics based on the type of the property.

The data file lists the following information: (ECON940)

First Column: PRICE (Price of the property in Australian dollars).
Second Column: TYPE (Type of the property: 1 for House, 2 for Unit).
Third Column: PROXIMITY (Proximity to the CBD: 1 for “up to 5KM”, and 2 for “Between 5KM and 10KM”).
Forth Column: BEDROOM (number of bedrooms: 1 for one bedroom, 2 for two bedrooms, 3 for three bedrooms and above). 
Fifth Column: BATHROOM (number of bathrooms: 1 for one bathroom, 2 for two bathrooms, 3 for three bathrooms and above).

See next pages for more information.
PART 1 (ECON940)
Calculate the Mean, Median, Standard Deviation, Coefficient of Variation and 95% population mean confidence intervals for property prices of Houses based on the following grouping:
Proximity of the property to CBD 
Note: Calculate above statistics for both “Up to 5KM” and “Between 5KM and 10KM”
Number of bedrooms 
Note: Calculate above statistics for “One bedroom”, “Two bedrooms” and “Three bedrooms or more”
Number of bathrooms 
Note: Calculate above statistics for “One bathroom”, “Two bathrooms”, “Three bathrooms or more”)

Note: In total, you need to show your results for 8 different categories. Provide all results in one table (see a sample table at the end of this document).
What conclusions can you draw from these analyses? Write a conclusion for this part. Also comment on the shape of distributions. 

PART 2 (ECON940)
Calculate the Mean, Median, Standard Deviation, Coefficient of Variation and 95% population mean confidence intervals for property prices of Units based on the following grouping:
Proximity of the property to CBD 
Note: Calculate above statistics for both “Up to 5KM” and “Between 5KM and 10KM”
Number of bedrooms 
Note: Calculate above statistics for “One bedroom”, “Two bedrooms” and “Three bedrooms or more”
Number of bathrooms 
Note: Calculate above statistics for “One bathroom”, “Two bathrooms”, “Three bathrooms or more”)

Note: In total, you need to show your results for 8 different categories. Provide all results in one table.
What conclusions can you draw from these analyses? Write a conclusion for this part. Also comment on the shape of distributions. 
PART 3 (ECON940)
Answer the following hypothesis testing questions:
Determine if average prices of units “within 5KM of the CBD” exceed average prices of units “located within 5 to 10KM from the CBD”.
Determine if average prices for House within 5 to 10KM of the CBD exceeds the average price of Unit within 5KM of the CBD.
Determine if average prices for “Houses with three bed rooms within 5 to 10KM of the CBD” exceeds the average price of “Units within 5KM of the CBD”.
Test the difference between population means of houses of the following groups: prices for “One bedroom”, “Two bedrooms” and “Three bedrooms (or more)” properties.
Test the difference between population means of units of the following groups: prices for “One bathroom”, “Two bathrooms”, “Three bathrooms (or more)” properties.

Write a conclusion for each part.
In addition, write an overall conclusion which combines all of the above parts (Parts 1-3).Be clear in the conclusion that you draw from your analysis, and provide useful suggestions to the company’s CEO. Conclusions must be based on the findings of your analysis only.
 

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