IDBQM001 Quantitative Methods for Business
2024-2025
Coursework Assignment
This assignment is worth 25% of the total marks.
Task:
The dataset representing the quarterly average rental prices for apartments in a fictional metropolitan area over the past 10 years (2014-2023). The data is categorised by three distinct neighbourhoods A, B and C, and for each neighbourhood, it is further divided into two apartment types: 1-bedroom and 2-bedroom apartments. Using the techniques taught in your course, analyse the data and provide insights.
You may choose to undertake some of the following tasks:
1. Calculate Rental Price Indexes: track the changes in average rental prices over time for each neighbourhood and apartment type.
2. Examine Correlations: Identify any potential correlations between rental prices of different apartment types within the same neighbourhood or between different neighbourhoods.
3. Forecast Future Rental Prices: Use regression analysis to predict future rental prices for each neighbourhood and apartment type.
4. Compare Neighbourhood Dynamics: Analyse and compare the growth rates of rental prices across the neighbourhoods and discuss the potential reasons behind any observed differences.
You should present your findings with appropriate visualisations and provide a summary of your key insights.
1000 words (plus appendices and references)
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<40
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40-50
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50-59
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60-69
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70+
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1. a)
Research paper
(~50%)
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Major sections
of the research paper are
missing.
No reference to context.
Does not refer to appendix.
No effort to
analyse results or make
suggestions for further study.
Appendix
disorganized and not
commented.
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Most sections of the research
paper are present.
Little reference to context.
Describes parts
of the appendix
material, rather than the
information displayed.
Appendix
referred to only sporadically.
|
All sections of the research paper are
present.
Generally, well written with
reference to context.
Analysis generally correct.
Appendix
referred to in text and
reasonable lay- out.
|
All sections of the research paper are
present.
Well written
with reference to context.
Results mostly
reasonable and sensible.
Some effort to look at
implications.
Written at a
level accessible to a non-
statistician.
Appendix
referred to in
text with a good lay-out.
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Clearly structured, signposted and well written with
continual reference to context.
Results are sensible and clearly
interpreted and explained.
Analysis goes
beyond context to look at implications of information
and/or forecasting (recommendations, further study, etc.)
Written at a level
accessible to a non- statistician.
Appendix referred to in text, clearly laid out and
commented.
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1. b)
Data
presentation (~50%)
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Graphs etc.
presented with no attempt to
improve on
default settings .
Graphs
inappropriate for goals.
Numerical measures
inappropriate and not
interpreted.
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Some attempt to format
output, but
poorly labelled, some output
inappropriate for goals, and do not add
much insight into the issues discussed.
Numerical
measures
inappropriate, or wrongly
calculated, or interpretation does not add much to
understanding of data.
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Most graphs
clearly labelled
and appropriate
for type of data and goals
Graphs
generally aid in
understanding of arguments made in the memo.
Numerical
measures and their
interpretations generally
correct and add some insight
into data.
Evidence of
some use of
basic Excel
Functions such as AVERAGE,
STDEV.
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All graphs
clearly labelled,
formatted and
appropriate for type of data
and goals.
Graphs aid in
understanding of arguments made in memo.
Numerical
measures and their
interpretations
mostly correct
and add insight into data.
Evidence of
some more
sophisticated
use of Excel
Functions using conditions.
|
All graphs clearly labelled and
appropriate for the type of data and
goals.
Creativity in
creating graphs to make the required points.
Graphs fully
support write-up.
Numerical
measures
interpreted well and contributed to
understanding.
Evidence of
appropriate and
sophisticated use of Excel Functions to analyse and present data.
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