BSAN2204 - Coding Documentation, Project Report (A2)
Briefing Notes
Dr. Thomas Magor
Background
The Coding Documentation Project Report (A2) documents the code used in your analysis of the Million
Song Dataset (MSD). It should include the code used to generate the outputs of the first Project Report
(A1), as well as extended analysis of the dataset using the methods learned in the latter half of the course.
The project should be submitted as a PDF document.
You are encouraged to use RMarkdown to compile your report.
Purpose
This purpose of this project is to provide both technical documentation of the R script used in your analysis
and demonstrate your ability to extend your analysis using the methods of business analytics taught in the
latter half of the semester (model validation, missing data analysis, dimensionality reduction).
The conclusion of this project should outline some possible strategic business decisions that a manager might
make based on your finalised analysis.
Suggested structure for the Coding Documentation Project Report (A2)
The Coding Documentation Project Report (A2) should have the following sections:
1. Data preparation and reconstruction
2. Exploring and visualising data
3. Predictive analytics
4. Conclusions
Data preparation and reconstruction
In the Data preparation and reconstruction section you should include the R script and output used to read
in the dataset, selecting a subset and treating missing data.
Describe the logic of the R syntax/functions used, what options (arguments) have been set, and what types
of input data (R objects) are used.
Provide basic interpretations in-text for the outputs.
Exploring and visualising data
In the Exploring and Visualising Data section you should include the R script and output used to generate
basic graphs and univariate/bivariate displays, measures of central tendency for your chosen output variable
as well as basic statistics (counts, proportions) that describe the dataset (using the subset selected following
your Data Preparation and Reconstruction steps).
1
Describe the logic of the R syntax/functions used, what options (arguments) have been set, and what types
of input data (R objects) are used.
Provide basic interpretations in-text for the outputs.
Predictive analytics
In the Predictive Analytics section you should include the R script and output to run linear regression,
extensions of linear regression and model validation (using the subset selected following your Data Preparation
and Reconstruction steps).
Describe the logic of the R syntax/functions used, what options (arguments) have been set, and what types
of input data (R objects) are used.
Provide basic interpretations in-text for the outputs.
Conclusions
The conclusion should outline some possible strategic business decisions that a manager might make based
on your finalised analysis.
Provide a succinct list of what you think your client should the prioritise first, second, third and describe
any potential limitations inherent in the analysis you have conducted (e.g., on the suitabiltity of the dataset
or other data quality issues) to support some suggestions for future directions you/someone else could take
with this dataset.
Submission Guidelines
The Coding Documentation Project Report (A2) is worth 50 percent of your score in BSAN2204 and is due
in Week 13 (check the eCP for exact date and time).
The report must be submitted as a PDF file. The use of RMarkdown is encouraged but is not compulsory
to receive a passing grade (you may compile your report using word processing software).
There is no word limit/lines of code limit, but you must be concise in your documentation.
Marking Criteria
The Coding Documentation Project Report (A2) will be marked against a marking rubric which includes
banded performance criteria for each section of the report, plus a criterion relating to the overall profession-
alism of your report. The rubric is available on BlackBoard.
The professionalism criteria includes both your use of appropriate language, but also your use of document
formatting and adherence to the submission guidelines.