IDBQM001 Quantitative Methods for Business

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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)

<40

40-50

50-59

60-69

70+

1. a)

Research paper

(~50%)

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.

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.

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.

1. b)

Data

presentation (~50%)

Graphs etc.

presented with no attempt to

improve on

default settings .

Graphs

inappropriate for goals.

Numerical measures

inappropriate and not

interpreted.

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.

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.

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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