QBUS

Topics: Statistics, Regression analysis, Statistical hypothesis testing Pages: 6 (1525 words) Published: October 31, 2014
QBUS5002: Quantitative Methods for Accounting
Semester 2, 2014
Group project
20% of final grade

General description
The group project is Compulsory. This means you must undertake the assessment otherwise you will receive zero marks (0) for this assessment. Note that this is a group assessment and you must work in a group of 3-4 students.

The group project is worth 20 marks (from the total mark of 100 marks for the unit). The deadline for submitting the assignment is 5pm, 31 October 2014. Assignments submitted later than the deadline will not be accepted and all group members will receive 0 marks. Your submission should take the form of a concise professional report and apply the following page set up and formatting:



Font: 12pt Times New Roman.



Margins: 2.5cm in all sides.



Line spacing: 1.5 lines.



Length: maximum 12 pages including any tables, graphs, appendices and references.

Failure to follow any of the above formatting instructions will result in an immediate penalty of 2 marks (out of 20).
There are two parts to the assignment:


Part A: Statistical analysis case study



Part B: Group organisation and contribution

The two parts are described in detail below.

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Part A: Statistical analysis (20 marks)
Business case information
A major hotel chain with hotels in a large number of major cities throughout the world is hoping to expand and wants to build a number of new hotels. Choosing the correct location is very important and for this purpose they have collected data on 80 randomly chosen hotels from their chain. The management are hoping to identify the key drivers of hotel profitability and to use these to help choose their next hotel location out of a few options currently available. For this purpose they require you to build a regression explaining hotel occupancy rates and have identified and collected the following variables for each of the 80 sampled hotels with the data based on the previous year’s hotel figures: Occupancy – ratio of the number of rooms occupied divided by the total number of rooms created and multiplied by 100 to make it into a percentage Rooms – number of rooms available for rent at the hotel

Comp – Competition measured as the number of hotel rooms within 10 kilometres Uni – number of university students in the city
Office – Office space in thousands of square metres in city Income – Average household income in the city
Beach – Distance to nearest beach in kilometres
Pool – 1 if hotel has a pool, 0 otherwise
The above variables are contained in the file ‘Hotels.xls’ on the spreadsheet entitled ‘Current hotels’. The hotel chain’s management has recently had a number of staff changes and so an initial descriptive analysis of the data is requested, to help provide an overview of the sampled hotels on the variables collected. For this purpose, both descriptive statistics and graphical techniques should be employed to highlight the main features of the data. The second aim of the study is to understand the main drivers of hotel occupancy rates through the use of a regression model between properly transformed variables. The management are familiar with regression techniques and but are not overly confident in interpreting the results or testing the model assumptions and so are requesting a fully motivated and interpreted regression with parameter significance and model specification

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tests provided. The regression should only contain variables shown to be relevant to determining hotel occupancy rates.
A further aim of the study is to help hotel management with the decision of whether plan to build a pool at the new location and believe the pool should only be built if it adds 5% or more to the overall occupancy rate. For this purpose they would like you to compare the average occupancy rate of hotels with pools to the average occupancy rate of hotels without pools using an appropriate hypothesis test. They would also like...
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