代写BUSS6002、代做Python编程设计

日期：2024-05-28 08:44

BUSS6002 - Individual Assignment

Semester 1, 2024

Due Date

• Due: before 23:59

1 on Wednesday 22 May 2024 (week 13).

• A late penalty of 5% per day applies if you submit your assignment late without a successful

special consideration or simple extension.

Rubric Overview

This assignment is worth 30% of the unit’s marks. The assessment is designed to test your

technical ability and statistical knowledge in modelling a real-world dataset, as well as your

communication skills in writing a concise and coherent report presenting your approach and

results. Refer to the Rubric later in this document for speciffc details.

Submission Instructions

You must submit:

• a written report (.PDF) with the following fflename format, replacing 1234134 with your

own student ID: BUSS6002 Report SID1234134.pdf.

• a Jupyter Notebook (.ipynb) ffle with the following fflename format, replacing 1234134

with your own student ID: BUSS6002 Notebook SID12341234.ipynb.

You may submit multiple times before the due date. Your latest submission before the due

date will be marked

2

. If you wish to re-submit after the due date please send an email to

[email protected] so that markers are notiffed of your new submission.

1You may submit up to 30 minutes late without penalty.

2The fflename on Canvas will change to include “-n” where n is the submission number. You can ignore this.

1Overview

On September 19, 2023 twitter user @purplepingers (Jordan van den Berg) launched shitrentals.org.

The site allows tenants to submit testimonies about landlords, property managers and rental

properties. The reviews are then publicly viewable and searchable with the address of the

property and the name of the agency visible. You have been given access to the data from

shitrentals.org

3

.

As a data-scientist-in-training, your task is to create a publishable research

report that investigates and reports on the factors that drive the perceived quality

of a rental property. The effect of each factor must be captured in a Generalized

Linear Model (GLM) of your choice. All analysis and model building must be performed

using Python and collated into a single Jupyter Notebook, which is to be submitted at the same

time as your report.

Report

Sections

A template for the report is provided in the assignment pack. Your report must contain:

• Abstract

• Introduction

• Methods

• Results and Discussion

• Conclusion and Limitations

• Bibliography

You may also include Appendices with additional details, ffgures and tables.

Requirements

• There is a limit of 2500 words for the report excluding tables, captions, bibliography and

appendices.

• Assume the reader of your report is a competent and trained data scientist or analyst.

They are familiar with the content of BUSS6002.

• All plots, computational tasks, and results must be completed using Python.

• Do not include any Python code as part of your report.

• All ffgures must be appropriately sized and have readable axis labels and legends (where

applicable).

Latex

Using LaTeX is highly recommended, though not required for this assignment. If you do not

have LaTeX installed locally we recommend that you use overleaf.com. All students can sign

up for an Overleaf Pro+ account via resource portal. If you’re new to Overleaf and LaTeX, help

is available via their free introductory course and tutorial video.

3The context for this assignment is real but the data is fake.

2Notebook

The submitted .ipynb ffle must

• contain all the code used in the development of your report,

• be runnable on an Ed environment, and

• must be free of any errors.

Data Description

The dataset contains 1000 property reviews collected between 1/1/2023 and 31/12/2023. To

simplify analysis the properties have been restricted to:

• Flats and Units

• 1 and 2 bedroom properties

• 3 suburbs close to the university (Camperdown, Redfern and Newtown).

Refer to the data dictionary for descriptions of the variables.

File Pack

A link to download the BUSS6002 Assignment Pack.zip is provided on canvas. The pack

contains:

• report/

– BUSS6002 Report SID1234134.tex (LATEXtemplate)

– IEEEtran.cls (LATEXstyle ffle)

– references.bib (BibTeX ffle)

• analysis/

– shitrentals.csv

– shitrentals dictionary.csv

– BUSS6002 Notebook SID12341234.ipynb (Jupyter Notebook Template)

Hints

The following resources may be useful:

• https://www.statsmodels.org/stable/examples/notebooks/generated/ordinal regression.html

• https://stats.oarc.ucla.edu/r/dae/ordinal-logistic-regression/

3Rubric

Criteria FA PS CR DI HD

Abstract and

Introduction

10%

The abstract is uninformative

and does not give readers a

clear understanding of the

paper’s content. It is missing

one or more of the following:

clear summary of purpose,

methods and results. The introduction does not

expand on the abstract by

providing a description of the

context of the paper or

motivation. The abstract is informative, giving readers some understanding of the paper’s content. It contains a mostly clear summary of the purpose, description of methods and results. The introduction expands on the abstract by providing a brief or vague description of the context

of the paper and

motivation. The abstract is informative, giving readers a clear understanding of the paper’s content. It contains a mostly clear summary of purpose, methods and results. The introduction expands on the abstract by providing a brief description of the context of the paper and motivation. The abstract is concise, informative, giving readers a clear understanding of the paper’s content. It contains a summary of topics, purpose, description of methods and results. The introduction expands on the abstract by providing a description of the context of the paper and motivation. The abstract is concise, informative, and engaging, giving readers a clear understanding of the paper’s content and significance. It contains a summary of topics, purpose, description of methods and results. The introduction expands on the abstract by providing a thorough description of the context of the paper and convincing motivation. Both of which are supported by

evidence from literature.Methods

40%

The description of the model

is either absent or severely

lacking, making it difficult to

understand its

implementation or rationale. Decision making lacks any

meaningful support from

evidence, with little to no

reference to data-based

exploration (EDA) or

established best practices. External resources are either

not cited or improperly

integrated into the discussion. The presented model, if any,

demonstrates a significant

mismatch with the problem

context: - the choice of the model is

inappropriate or irrelevant to

the problem context - variables are either poorly

selected or not utilized at all - there is no effort to control

for variables not of direct

interest to the study - overfitting is not addressed

A rudimentary description

of the model is provided. Decision making attempts

to be supported by

evidence, but the

justification is minimal and

may rely more on intuition

than on data-based

exploration (EDA) or

established best practices. External resources are

cited sporadically, with

limited integration into the

discussion. The presented model: - is appropriate for the

problem context but lacks

explanation and

justification - uses only a few variables

to enhance predictive

performance, with

significant missed

opportunities or variables

not adequately leveraged - displays limited effort is

made to control for

variables not of direct

interest to the study - gives minimal attention

to overfitting, with little

validation or discussion

provided

A description of the model is

provided, though it may lack

depth or thoroughness. Decision making is

attempted to be supported

by evidence, but the

justification may be limited or

not fully grounded in

data-based exploration

(EDA) or established best

practices. External resources

are cited, but the integration

may be less seamless or

comprehensive. The presented model: - appropriate for the problem

context - generally plausible for the

problem context, but there

may be some gaps in

explanation or justification. - uses some but variables to

enhance predictive

performance, but there may

be missed opportunities or

variables not fully leveraged. - attempts to control for

variables not of direct

interest to the study, though

some could be more

rigorously addressed - attempts to not overfit to

the data, but lacks

thoroughness

A detailed description of the

model is provided. Decision

making is supported by

evidence, through data-based

exploration (EDA) or

reference to course materials

or external resources,

although some areas may

lack thorough justification. External resources are cited

appropriately. The presented model: - is appropriate for the

problem context - is plausible based on the

problem context, though

some aspects may require

further justification - uses of most variables to

enhance predictive

performance, though there

may be some missed

opportunities or oversights

(model selection) - controls for variables not of

direct interest to the study,

though some could be more

rigorously addressed - is shown to not overfit to the

data (validation)

A comprehensive and

detailed description of the

model is provided. Decision

making is thoroughly justified

through data based evidence

(EDA) or established best

practice provided by course

material or external

resources. External

resources are cited

appropriately. The presented model: - is appropriate for the

problem context - is plausible based on

problem context - makes full use of all

variables to maximise

predictive performance

(model selection) - controls for variables, which

are not of interest to the

study - is shown to not overfit to the

data (validation)Results

20%

The results section

inadequately presents

findings from the research,

with minimal to no discussion

of model outputs. The

interpretation demonstrates a

lack of understanding of the

implications within the

problem context, with little to

no attempt to relate findings

to the context.

The results section

presents basic findings

from the research, with

limited discussion of

model outputs. The

interpretation

demonstrates a

rudimentary

understanding of the

implications within the

problem context, but lacks

depth or thorough

exploration.

The results section presents

an analysis of the research

findings, accompanied by a

discussion of model outputs.

The interpretation

demonstrates a basic

understanding of the

implications within the

problem context, though

there may be limitations in

depth or clarity.

A detailed analysis of the

research findings is provided,

accompanied by a

substantive discussion of

model outputs. The

interpretation demonstrates a

solid understanding of the

implications within the

problem context, though there

may be areas where further

depth or clarity could enhance

the analysis.

A comprehensive and

insightful analysis of the

research findings is provided,

including a thorough

discussion of model outputs.

The interpretation shows a

good understanding of

implications within the

problem context.

Conclusion and

Limitations

10%

Fails to effectively summarise

the key findings of the study,

providing readers with a

vague or incomplete overview

of the research outcomes.

Limitations, if acknowledged,

are addressed inadequately

or may be entirely omitted,

demonstrating a lack of

awareness or understanding

of the study's constraints.

Suggestions for future

research directions are

absent or poorly articulated.

A rudimentary summary of

the key findings of the

study is provided, offering

readers a basic overview

of the research outcomes.

Limited acknowledgments

of limitations may be

included, indicating some

recognition of the study's

constraints, though they

may lack thorough

exploration. Suggestions

for addressing these

limitations in future

research, if present, are

brief and may lack

specificity.

A basic summary of the key

findings of the study is

provided, offering readers a

general overview of the

research outcomes. Some

acknowledgments of

limitations are included,

indicating a basic awareness

of the study's constraints.

Suggestions for addressing

these limitations in future

research are briefly

mentioned, but they may

lack depth or specificity.

An effective summary of the

key findings of the study is

presented, providing readers

with a clear overview of the

research outcomes.

Limitations are

acknowledged, indicating an

understanding of the study's

constraints and challenges.

Suggestions for addressing

these limitations in future

research are presented,

although they may lack

in-depth exploration or

specificity.

An effective summary of the

key findings of the study is

presented, providing readers

with a clear overview of the

research outcomes.

Limitations are

acknowledged, indicating an

understanding of the study's

constraints and challenges.

Suggestions for addressing

these limitations in future

research are provided.Report Presentation

10%

Formatting is unclear, illogical

or inconsistent.

The figures produced are of

sub standard quality.

Grammar and spelling pose

significant barriers to the

reader’s comprehension.

References do not follow a

consistent format e.g. APA

6th or 7th.

Formatting is mostly clear,

logical and consistent.

Writing presents a small

barrier to the reader’s

comprehension.

Visuals produced are of

poor visual quality.

References mostly follow

a consistent format e.g.

APA 6th or 7th.

Formatting is clear, logical

and consistent.

Writing contains some

grammatical or spelling

errors, but none that pose

any significant barrier to

reader comprehension.

Visuals produced are of

average visual quality.

References mostly follow a

consistent format e.g. APA

6th or 7th.

Formatting mostly follows

best practice of a research

paper i.e. uses LaTeX or

similar professional

typesetting.

Writing demonstrates

outstanding precision, clarity,

and concision.

Visuals produced are of good

visual quality and easy to

read.

References follow a

consistent format e.g. APA

6th or 7th.

Formatting follows best

practice of a research paper

i.e. uses LaTeX or similar

professional typesetting.

Writing demonstrates

outstanding precision, clarity,

and concision.

Visuals are of high quality

and increase the reader’s

understanding.

References follow a

consistent format e.g. APA

6th or 7th.

Notebook

10%

Features of the Jupyter

Notebook are not used

appropriately. The notebook

is incoherent. Code is hard to

read, poorly or inconsistently

formatted and no attempt has

been made at

documentation.,

Features of the Jupyter

Notebook are used mostly

appropriately. The

notebook is formatted

poorly. Code is reasonably

clear with inconsistencies

in places.

Features of the Jupyter

Notebook have been used

appropriately. The notebook

is formatted acceptably.

Code is clear with some

evidence of best practices.

Jupyter Notebook is

runnable without error.

Features of the Jupyter

Notebook have been used

appropriately. The notebook is

well laid out and formatted.

Code is clear, consistent and

follows the majority of best

practices.

Features of the Jupyter

Notebook have been used to

pleasing effect. The notebook

is well laid out and formatted.

Code is clear, consistent,

follows best practices,

descriptions and comments

are excellent.