Assessment 1: Industry-based Individual Report

Week 4: 5:00 pm Friday 6th October (AEDT)

20%

Writing and programming tasks, based on a case study

Maximum count of 3 pages, excluding references, figures, tables, and appendices

Via Moodle course site, through Turnitin

Background

Description of assessment task

In this short individual assignment, you are a junior data analyst working for a food delivery business.

Your task is to undertake an exploratory data analysis using R to investigate factors influencing food delivery speed.

You are provided with a dataset based on a food delivery company based in India. The dataset is available on Moodle and consists of 31,368 food deliveries completed between 11 February 2022 and 6th April 2022. The data attributes are displayed in the data dictionary in Appendix A of this document.

- A summary of descriptive statistics of relevant variables in the dataset and why you think such variables are relevant to your analysis.

- Description of data aggregations that you deem necessary to conduct your analysis.

- A visual data analysis, using predominantly multivariate bar charts and boxplots to identify FOUR (4) relevant factors impacting food delivery speed.

- Interpretation of your findings and actionable insights that you could derive to help food delivery businesses improve their performance.

- Offer a maximum of three recommendations to the leadership, as supported by your insights and analysis and referenced with the industry’s best practices.

Dataset and data dictionary

Tips for analysing the data and writing your report.

Here is advice from the lecturing team on exploring the dataset:

1. It is important to emphasize that there is no single standard answer to the assignment. There are lots of different dimensions of the data to explore, and some aspects and dimensions of the data are likely to be more useful than others. Thus, it is important that before starting your assignment, you systematically explore the different variables in the dataset.

2. To help focus your analysis and insights, think of potential problems that could drive food delivery speed. Asking questions, like “Are there differences across location types, order types, etc. for key factors that may drive food delivery speed?”, can help provide greater structure for the analysis.

3. Although you may create many graphs for your assessment (e.g., histograms to better understand the data), you only want to include figures that support your main findings. These graphs should summarize the relationships that you are reporting on or analyzing. As guidance, not more than four charts must be included in the main report. The remaining non-relevant charts can be included in the appendices.

4. Also, look for potential outliers in the dataset. What can we infer from these outliers? Do these outliers represent situations that are more prone to faster/slower deliveries? Should the outliers be included in the analysis of the data? Any decisions made about including or not including  outliers should be justified in the report.

Requirements:

• Explore and understand the business problem in the industry/country context.

• Clearly state the purpose of the analytics tasks.

• Apply appropriate three data exploration techniques, such as summary statistics, data visualisation, and diagnostics analysis. Avoid conducting predictive or prescriptive analytics.

• Generate graphs, such as histograms, bar charts, scatter plots, and box plots, using R, to explore associations between variables.

• Interpret the results obtained from the analytics.

• Provide recommendations based on the analytics results.

• Support the recommendations using state-of-the-art industry practices and/or academic references.

• Incorporate supplementary readings related to the assessment and conduct self research to develop informed recommendations.

• Demonstrate proficiency in reading and writing in English.

• Use language, figures, and/or tables to convey qualitative and quantitative information effectively and accurately.

• Attach the R programming code (not a screenshot but a copy of the R-scripts) to the Appendix of your report.

5. Organization and structure of the report (10%)

• Develop a logical structure to organize the sections of the report.

• Use academic referencing in the Harvard style. Refer to the UNSW guideline: https://www.student.unsw.edu.au/harvard-referencing

• An example of structuring and developing the report is provided in Appendix B. N.B: The marking rubric is displayed on the last page of the document in Appendix C.

Submission instructions

1. Late submission will incur a daily penalty of 5% of the available marks for the assignment or part thereof (including weekends) from the due date and time. An assessment will not be accepted after 5 days (120 hours) of the original deadline unless special consideration has been approved. An assignment is considered late if the requested format, such as hard copy or electronic copy, has not been submitted on time or where the ‘wrong’ assignment has been submitted.

2. No extensions will be granted except in the case of serious illness, misadventure, or bereavement, which must be supported with documentary evidence. Requests for extensions must be made to the Lecturer-in-charge by email and be accompanied by the appropriate documentation no later than 24 hours before the due date of the assignment. In circumstances where this is not possible, students must apply for Special Consideration.

3. The Course Convenor is the only person who can approve a request for an extension. If you do request an extension, the Course Convenor will email you with the decision. Note: A request for an extension does not guarantee that you will be granted one.

Word Limit Penalties

Studiosity English Support

AI Tools and Academic Integrity

The use of AI or ChatGPT to help you learn the R codes is encouraged. However, the use of ChatGPT for writing the report will be subject to an AI-detective tool, which may lead to academic integrity investigations. In general, you must comply with academic integrity and avoid all forms of plagiarism.

This includes buying essay/writing services from third parties, and engaging another person to complete your assessment, whether the latter is paid or not.

Appendix A: Data Dictionary

Appendix B: An Example of the Report Template

• Page numbers from this page onwards (Insert à Page Number)

• A header from this page onwards, including your ZID and course code (Insert à Header)

• All key sections and sub-sections of your report are listed on the contents page.

If you are unsure how to format a report contents page, select “References” in the menu above, then “Table of Contents”. Examples: