Management homework Assignment

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.

3

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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