Faculty of Information Technology
FIT4005 / FIT5125
Research Methods for IT
Semester 1 2024
Assignment 3: Weeks 8 & 9
- a separate PDF for the exercises for Week 8 & 9.
Week 8 Descriptive Statistics |
Week 9 Inferential Experiments |
Weighting: 20 marks |
Weighting: 20 marks |
See page 3. |
See Page 5. |
⚐ Marking guides to help you position your work are available on Moodle.
⚐ There are specific requirements for file names on your submission (see the instructions for each exercise).
- Content and completeness of tasks
- Clarity and relevance of content
- Level of critical analysis
- Logical structure and organization of ideas
- Use of references (where appropriate)
- Format, grammar, spelling etc.
2. Note that plagiarism detection procedures may be applied to each submission. See the University rules and regulations regarding plagiarism and resulting penalties. Any case of plagiarism detected will mean automatic failure of the entire assignment. Note that even where TurnitIn reports a non-trivial similarity score, this may simply be the result of text that is part of the original question or answer template (this is not a problem).
3. Late submissions will incur a penalty of 10% per day, see:
- Student's name
- Student ID number
- Tutor's name
- Studio name
Telling a coherent story with your data is a core part of the research process. Statistics can be used in myriad ways to describe any given dataset, so it is important to use the appropriate measures and visualisations to enrich and provide context to a narrative of your data. Although in a perfect world we would ask a question and then design a process to capture data that answered that question, in reality we often have to make use of 'secondary' data, or data captured previously.
In this assignment, you will tell a story about some public data using the methods you have learned about.
1. Identify a data source from one of the following open data repositories:
- https://www.data.vic.gov.au/
- https://www.abs.gov.au/statistics/
- https://uis.unesco.org
- https://ec.europa.eu/eurostat/databrowser/
- https://opendata.cityofnewyork.us/
2. Formulate a research question that you want to ask of this data - for example "What is the relationship between the value of imported goods and cost of living?" (max. 50 words)
3. Select 2 appropriate descriptive metrics (e.g. mean) that tell you something about the data, and calculate those metrics on your selected data, using a tool of your choice. Present the fields from the dataset used and the resulting calculated values (max. 50 words)
4. Create an appropriate visualisation to help a reader understand what you are saying about the data. The visualisation should be fully annotated.
5. Write a short narrative description of your findings as they relate to you research question, referencing both your chosen metrics and visualisation. (max. 150 words)
What to Submit |
1. A PDF document, named "STUDENT-ID-Week8.pdf" containing the responses to the assignment and a CSV or JSON file containing the dataset you used. |
How Much to Write
There is a strict word limit for your answers detailed above. For submission over the specified word limits, only the parts of answers within the word limit will be awarded marks.
What to Know |
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What to Submit |
1. A PDF containing your answers to the questions named "STUDENT-ID-Week9.pdf". |
How Much to Write |
There is a strict word limit for your answers detailed above. For submission over the specified word limits, only the parts of answers within the word limit will be awarded marks. |
What to Know |
|