COMM5000 Data Literacy Term 1, 2024

Term 1, 2024

Assessment Administrative Details

Turnitin

Turnitin is an originality checking and plagiarism prevention tool that enables checking of submitted written work for improper citation or misappropriated content. Each Turnitin assignment is checked against other students' work, the Internet and key resources selected by your Course Coordinator.

If you are instructed to submit your assessment via Turnitin, you will find the link to the Turnitin submission in your Moodle course site. You can submit your assessment well before the deadline and use the Similarity Report to improve your academic writing skills before submitting your final version.

You can find out more information on the Turnitin information site for students.

Late Submissions

The parameters for late submissions are outlined in the UNSW Assessment Implementation Procedure. For COMM5000, if you submit your assessments after the due date, you will incur penalties for late submission unless you have Special Consideration (see below). Late submission is 5% per day (including weekends), calculated from the marks allocated to that assessment (not your grade). Assessments will not be accepted more than 5 days late.

Special Consideration

Special consideration is the process for assessing the impact of short-term events beyond your control (exceptional circumstances), on your performance in a specific assessment task.

What are circumstances beyond my control?

These are exceptional circumstances or situations that may:

• Prevent you from completing a course requirement,

•     Keep you from attending an assessment,

• Stop you from submitting an assessment,

• Significantly affect your assessment performance.

Available here is a list of circumstances that may be beyond your control. This is only a list of examples, and your exact circumstances may not be listed.

You can find more detail and the application form on the Special Consideration site, or in the UNSW Special Consideration Application and Assessment Information for Students.

MILESTONE 2: Case Study Project Proposal

Report details

Week 7, Sunday 31th March 11:59PM

20%

Report: This is individual work. Reports will be checked for plagiarism.

1000-1500 words (not including tables, graphs, and references)

Via Moodle course site

Description of assessment task

In M1, you have spent time understanding the dataset of your assigned country or countries. M2 aims to use hypothesis testing to explore some of the patterns you may have observed in your analysis in M1.

To address the question of whether the profitability of wholesale distribution companies differs by country of jurisdiction, we can check bar charts of key profitability variables first by country and for some industries.   This is what some of you were able to do in M1, and others will be describing while preparing for M2. However, this descriptive analysis needs to be given a statistical analysis. This will be achieved by conducting significance hypothesis tests to evaluate the evidence from the data and measure uncertainty around the conclusions made.

(A) Country and profits variables

For M2, you are required to consider the following:

Profitability variables:

-     Operating Revenue ($’000)

-     EBITDA: earnings before interest, taxes, depreciation, and amortisation

https://www.investopedia.com/terms/e/ebitda.asp

Countries:

Each student MUST use the TWO countries assigned to then in the data allocation spreadsheet for M1.

Note: Those who want to prepare an analysis for PwC showcase should add at least one more country (of

your choice) to the analysis. We will select some of these M2 reports and send to PwC for feedback. But this

will not affect the grade of M2! (PLEASE IGNORE IF YOU ONLY WANT TO DEAL WITH THE COURSE REQUIREMENT)

(B) Industry Classification

A random selection of THREE industries have been allocated to you in the Country/Year/Industries allocation M2. Please check that your name is in the sheet. If not email [email protected] ASAP!

Choose TWO industries of the three to analyse for M2. The third will be added to the analysis in final report.

(C) Economic Indicators data:

- Clearly state your null hypothesis, and especially the alternative(s). One-sided alternatives may be useful in driving links between a country's economic conditions and its wholesale companies' profitability.

For example, if you are testing a null that average profits are the same in China and Australia, but you reject in favour of a one-sided hypothesis that profitability is larger/or smaller in Australia. You may try to check what differs in between China and Australia in terms of their key economic indicators. If Australia’s GDP growth is higher in that year and you suspect that to be driving higher profits, you can argue for an ‘>’ alternative in favour of Australia.  If you do not believe there is any argument for a one-sided alternative, then a two-sided is fine. It

- Explain the rationale of the test statistic and present your test’s finding using the  p-value method.   Your analysis should show that you understand the assumptions behind the tests and the considerations around type

1 and type 2 errors in this case.

This doesn’t need to be long but stated in your description of what you will achieve from significance hypothesis testing for both the country effect and the Covid effect. Remember to state any statistical considerations that may make your tests poor regarding power.

You may choose to present your test decision for the 2 countries in a table:

Table 1: Country Effect summary results of hypothesis testing

You can do the same to summarise your test results for the Covid effect (by country).

Table 2: Covid19 Effect summary results of hypothesis testing for ‘Country 1’

Table 3: Covid19 Effect summary results of hypothesis testing for ‘Country 2’