Management homework Assignment
This assignment covers material from Sessions 1-4 and is worth 20% of your total mark
of BBS300. Your solutions should be properly presented, and it is important that you
double-check your spelling and grammar and thoroughly proofread your assignment
before submitting. Instructions for assignment submission are presented in
the “Assignment 1” link and must be strictly adhered to. No marks will be
awarded to assignments that are submitted after the due date and time.
All analyses must be carried out using SPSS, and no marks will be awarded
for assignment questions where SPSS output supporting your answer is not
provided in your Microsoft Word file submitted for the Assignment.
Questions
In this assignment, we will examine the “Real Estate Market” dataset (described at the
end of the assignment ) and “Employee Satisfaction” dataset. Before beginning the
assignment, read through the descriptions of these dataset and their variables carefully.
The “Real Estate Market” dataset can be found in the file “realestatemarket.sav,” and
the “Employee Satisfaction” dataset can be found in the file “employeesatisfaction.sav.”
You will need to carefully inspect both SPSS data files to be sure that the
specification of variable types is correct and, where appropriate, value
labels are entered.
1. (12 marks)
2
Use appropriate graphical displays and measures of centrality and dispersion
to summarise the following four variables in the “Real Estate Market” dataset. For
graphical displays for numeric data, be sure to comment on not only the shape of
the distribution but also compliance with a normal distribution. Be sure to
include relevant SPSS output (graphs, tables) to support your answers.
(a) Price.
(b) Lot Size.
(c) Material.
(d) Condition.
2. (8 marks)
Again consider the variable Price, which records the property price (in AUD). It
is of interest to know if this is associated with the distance of the property is
located to the train station. It is also of interest to know if the property
prices are associated with distance to the nearest bus stop. Carry out
appropriate statistical techniques to assess whether there is a significant
association between the property price and distance to the nearest train (To train)
station and the nearest bus stop (To bus). Be sure to thoroughly assess the
assumptions of your particular analysis, and be sure to include relevant SPSS
output (graphs, tables) to support your answers.
3. (7 marks)
Consider the “Employee Satisfaction” dataset, which asked participants to provide their
level of regularity to a series of thirteen statements. Conduct an appropriate analysis
to assess the reliability of responses to these statements. If the reliability will
increase by eliminating one or more variables, report which variable(s) this is/are.
Again, be sure to include relevant SPSS output (graphs, tables) to support your
answers.
4. (3 marks)
Presentation marks. These marks are allocated based on:
• structure, clarity, and tidiness of presented solutions/answers; and
• correctness in spelling and grammar.
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Melbourne Property Prices
The dataset realestatemarket.sav contains data on 120 properties listed on the database
of a real estate agent in an Australian suberb. The table b e l o w p r o v i d e s a list of
variables contained in the dataset.
Variable Descriptions
Price Selling price of house in $’000
Rooms Number of main rooms in the house
Lot Size Area of the block of land (lot) in square metres
Age Age of the house in years
Area Area of the house in square metres
Material Timber = 1, Veneer = 2, Brick = 3
To Train Distance of the house to the nearest train station (kilometres)
To Bus Distance of the house to the nearest bus stop (kilometres)
To Shops Distance of the house to the nearest shopping centre (kilometres)
Street Street appeal as evaluated by the real estate agency:
ranges from 0 (lowest appeal) to 10 (highest appeal)
Storeys Number of storeys or levels in the house
Style Traditional Style = 0, Non-Traditional Style = 1
Bedrooms Number of bedrooms
Bathrooms Number of bathrooms
Kitchen Style of kitchen: Adequate = 0, Modern = 1
Heating Central or other heating system installed: No Heat = 0, Yes Heat = 1
AirCon Air conditioning installed: No AC (No AirCon) = 0, AC (Yes AirCon) = 1
Bay Views Proportion of views of the Bay from a prominent part of the property:
ranges from 0 = Nil views up to 1 = Full views
Suburb Three different suburbs: 1 = Suburb A, 2 = Suburb B, 3 = Suburb C
Weekly Rent $ Actual or estimated weekly rent in $.
Rental Return % Annual rate of return from rent income (Weekly rent x 52)/(Price in $’000) as a percentage (%)
Condition The condition of the house in general. Very Poor = 1, Poor = 2, Good = 3, Excellent = 4
Rental Status Vacant (available for rent) = 1; Rented (currently rented) = 2; Owner (occupied by owner) = 3
Table 1: Descriptions of variables contained in the dataset Realestatemarket.sav
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