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Marking Rubrics.....................................................................................................................................................................................................................8

Assessment Summary

* Due dates are set at Australian Eastern Standard/Daylight Time (AEST/AEDT). If you are located in a different time-zone, you can use the time and date converter.

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

Extensions

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.

CASE STUDY INFORMATION

Case/Scenario: You consult the funds management on their prospective international portfolio investment strategy. The fund managers that you work with regularly have commissioned you to provide an overview of the specific industries. Currently, the fund management is interested in cross-border services industry as one of the prospective investment directions. They want to identify historical performance and future projections of the industry in Europe, the United States, and Asia-Pacific regions.

Business context: The cross-border services industry thrives on the exchange of skills, knowledge, and expertise across borders, generating significant employment opportunities and contributing substantially to the GDP of both exporting and importing nations. This industry's growth has been fueled by advancements in technology, the expansion of global supply chains, and the increasing demand for specialized services in a rapidly changing world.

1. Looking at both industry and economy specific data over the past five years, is there a correlation (positive or negative) between the performance of cross-border services industry and their local jurisdiction’s GDP and other key economic metrics or events (e.g., the COVID-19 pandemic). If so, what may be the reasons for the correlation? Please provide both quantitative and qualitative analysis supporting any findings.

2. In addition, based on your analysis towards the Objective (1) identify future prospects, drivers of performance and risks across various jurisdictions? Please also provide any supporting analysis for these additional considerations. The key jurisdictions of interest are the US, UK, China, Japan, South Korea, Australia, and New Zealand.

COMM5000 Context

This is a business question that is based on real datasets. The role you are to play is one of a consultant contracted by funds management to assist with the analysis of data using the COMM5000 data analysis tools, which include descriptive and inferential statistics.

The work will be scaffolded into two milestones M1 (20%) & M2 (20%)) and a final project report (60%). Every milestone will require you to use what you have learned to address specific aspects of the data. Generally, M1 consists of an exploratory data analysis, whereas M2 is concerned with identifying hypotheses and formulating key inferential questions. In the final project report, all the insights gathered from M1 and M2 are used to model the data to answer the project questions.

Schedule of engagement

As part of additional support for assessments one of the course teaching team members will hold consultation sessions throughout the term. It is very important that you attend these sessions where we will hold live synchronous sessions to provide more detailed information about the case study. During these sessions, you are free to ask questions and discuss any aspects of the project.

Week 4, Friday 6th October 5PM

20%

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

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

Via Moodle course site

1) Correlation analysis: a cross-sectional analysis of correlation patterns between the performance of crossborder services industry and the local jurisdiction’s key economic factors like GDP.

2) Covid-19 effect analysis of cross-sectional patterns across the years may capture the effect of Covid on performance of the industry (by country).

You must submit a written development plan summarising the finding from the data explorations, describing any patterns from comparing summary statistics of the variable of interest between countries, and providing a plan on how you may address the key questions (1) and (2). The report should be concise and to the point.

Please note that you are not required to fully answer (1) and (2) in this milestone. Instead, you are required to develop insights and understand the problem, as well as the datasets for your final project.

Approach to the assessment task

Country allocation

(ii) Data preparation. Please check the document ‘Data Preparation and Data Cleaning’ to prepare your data for analysis. The main data issue here is the missing points. These appear as ‘n.a.’ but sometimes also as ‘0’. In the latter case, you should double-check whether the variable in question can have a ‘real’ 0 value or whether ‘0’, in fact, represents an ‘n.a.’ missing value. Some strategies for dealing with missing points appear in the document and will be discussed in your weekly SEM. You must explain any data manipulations you perform and provide a rationale for them.

(iii) Variables of interest. While preparing the data, think about (1) and (2) above and ask what information you need to be able to address these points. For instance, one of the datasets contains annual bilateral data on annual international trade in services by various characteristics.

(iv) Data structure. An essential aspect of the analysis is understanding the dataset's structure. Each of the datasets contains notes with the description of variables and their structure. For each country, we have a panel dataset. Each panel is a cross-section of companies observed over a period of years.

(v) You may not have all the information needed in the data file to address (1) and (2). For example, we are interested in understanding the effect of a country's key economic indicators (like GDP) on the services industry. At this point, you may want to ask how to use additional data to answer this question. By the completion of the final project you will be required to obtain additional data from other available sources.

The written work must provide a brief description of the Case Study problem and a clear plan of how the dataset provided will address the key questions raised in the project description. You will have the opportunity to adjust, revise and review this plan as we progress throughout the term. M1 analysis is based on COMM5000 content covered in weeks 1, 2 and 3.

(i) Numerical summaries of the key variables of interest: present the means, median, and standard deviations of the variables in the data. You may represent these results in the form of tables. For example, for each country

(ii) Graphical representations of some variables if you deem it important for to capture a trend or some interesting patterns in the data. For instance, if you plot a bar chart of average trade performance by country and by year, there may be a pattern emerging in relation to jurisdiction and year effect.

(iii) What conclusions can you make from the inspection of these data summaries in the form of tables and graphs? For example, is there a pattern in the tables when comparing the countries?

(iv) Your analysis should inform your development plan to address points (1) and (2) in Milestone 2 and in the final report. This plan may be revised later during your work on Milestone 2.

* Introduction You should briefly introduce the industry client (funds management) and summarise the purpose and importance of this project for the client. Then outline how this preliminary insight development plan will be structured. It is important to provide some background information on this topic, which is to say, what is the general performance of7 cross-border services industry.

* Data Summaries and Descriptive Statistics: Provide the necessary analysis to explore the variables in each country. Describe the trends and stories that emerge from the data summaries. Are any patterns emerging from the graphs or tables you have constructed so far? Note: now that you have completed the first stage of data summaries, you have some basic insight into the dataset. You can use this information to develop some plans of action to address points (1) and (2) in Milestone 2 and in the final report.

* Conclusion: This should summarise the findings of your investigation and any concluding comments. The conclusion should also provide your plan for the next step of the analysis.

* It is suggested that you limit your report to a maximum of 8 pages including tables, graphs, and references.

- Weekly seminar: the seminar coordinator will cover aspects of data manipulation using Excel during the SEM session

Milestone 1 Marking Rubrics