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代寫FIT5147調試 Data Exploration Project

FIT5147 Initial Project Proposal and Data Exploration Project

In this project, you are asked to analyse and explore data or topic of your choice.
Please note that your project is subject to tutor’s approval. ?Do not seek approval from the lecturers?!
It is an ?individual assignment? and ?worth 35%? of your total mark for FIT5147.

Relevant learning outcome
● Perform exploratory data analysis using a range of visualisation tools.
Overview of the tasks
1. Identify the project ?topic?, ?questions? that you want to address, and ?data? source(s).
2. Submit ?Initial Project? ?Proposal? in the Assessment block of Moodle by the end of Week 3.
3. Wait for approval before proceeding further. You will receive the feedback within Week 4.
4. Collect data and wrangle it into a suitable form for analysis using whatever tools you like.
5. Explore the data to answer your original question and/or to find something interesting using
Tableau or R. The exploration should use appropriate visualisations and statistical tests.
6. Submit a report detailing your findings and the method that you use.
7. The Data Exploration Report? is due on Monday of Week6.
Initial Project Proposal (2%)
Write a document consists of the following sections:
1. Project title.
2. Your identity (full name, student ID, tutor name).
3. 1-3 questions you wish to answer. The number of questions depends on the scope of the
question itself. You can have one general question or three more detailed ones.
4. Data source(s) you plan to use to answer these questions.
Brief description of the data in each data source (kind of data: tabular, spatial, network,
textual or other, number of records, URL).
Data Exploration Report (33%)
The written report should be ?no more than 10 pages?. It must follow the following format.
1. Introduction
Problem description, question and motivation.
2. Data Wrangling
Description of the data sources with links if available, the steps in data wrangling (including
data cleaning and data transformations), and tools that you used.
3. Data Checking
Description of the data checking that you performed, errors that you found, your method to
correct them, and tools that you used.
4. Data Exploration
Description of the data exploration process with details of the statistical tests and
visualisations you used, what you discovered, and tools that you used.
5. Conclusion
Summary of what you learned from the data and how your data exploration process
answered (or didn’t) your original questions.
6. Reflection
Brief description of what you learned in this project and what in hindsight you might have
done differently.
7. Bibliography
Appropriate references and bibliography.
Your written report will be the sole basis for judging the quality of the data checking, data wrangling
and data exploration as well as the degree of difficulty. Thus, please include sufficient information in
the report. It should, for instance, contain images of visualisations used for exploration and the
results of any tests, even if they are negative.
Marking Rubric:
Initial Project Proposal:
● clear question, identification of suitable data sources) [2%]
Data Exploration Report:
● Data checking and wrangling (appropriate checking, cleaning and reformatting, managing to
get data into Tableau or R) [5%]
● Data exploration (completeness/thoroughness, use of appropriate visualisations and
statistical measures, identification of trends or patterns etc and clearly articulated findings
and limitations) [10%]
● Degree of difficulty (e.g. use of non-tabular data, significant wrangling or cleaning required,
large dataset, multiple data sets) [13%]
● Written report (quality of writing and use of images etc, logical structure, completeness)
[5%]
Due dates:
● Submit the ?PDF ?version of the ?Initial Project Proposal? document to Moodle by ?Sunday, 5
April 2020, 11:55 PM?.
● Submit the ?PDF ?version of the ?Data Exploration Report? document to Moodle by ?Monday, 27
April 2020, 4:00 PM?.
Late submissions
● We encourage everyone to submit the proposal on time. We give 0 mark for late Initial
Project Proposal submission. Everyone must submit the Initial Project Proposal, even when
the deadline has passed because your project must be approved before you can continue
working on the Data Exploration Report.
● The late penalty for Data Exploration Report is 2% of 33 mark per day.


Example of Initial Project Proposal:

Initial Project Proposal
Causes of serious bicycle accidents

Name : AAAAAA AAA
Student ID : 11111111
Tutor : TTT TTTTTT

Questions
1. What are the most common kinds of serious bicycle accidents?
2. How do lighting conditions affect these accidents?
Data sources:
a. ACT Road Cyclist Crashes, since 2012, which have been reported by the Police or the Public
through the AFP Crash Report Form.
b. Canberra’s sunrise and sunset times for 2018.
The data source a will allow me to answer question 1 at least for the ACT, while the combination of
data source a and b will allow me to answer question 2.
Description of data sources:
1. Tabular data: 1K rows x 11 columns It has both spatial and temporal attributes as well as
some simple text
(https://www.data.act.gov.au/Justice-Safety-andEmergency/Cyclist-Crashes/n2kg-qkwj)
2. Tabular data in HTML: ~400 rows and 11 columns
(http://members.iinet.net.au/~jacob/risesetcan.html)

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