INSTRUCTIONS TO STUDENTS:

1. This End-of-Course Assessment paper comprises 5 pages (including the cover page).

2. You are to include the following particulars in your submission: Course Code,
Title of the ECA, SUSS PI No., Your Name, and Submission Date.

3. Late submission will be subjected to the marks deduction scheme. Please refer to the Student Handbook for details.

Question 1

School A utilizes a combination of IoT sensors and wearable technologies to monitor behavioral and physiological data for 100 students over a 30-day period. The collected data include facial expressions, posture, movement, heart rate, skin temperature, and breathing rate. Additionally, classroom environmental factors such as noise levels and lighting are recorded. Attention, engagement levels, and inactivity are classified based on the gathered data. A detailed data dictionary is available on the second sheet of the provided Excel file.

Question 1a

Identify one (1) business problem that can be addressed by analysing the data. Elaborate on the related data fields and how they can provide insights to address the problem. (Max word count: 100 words) (15 marks)

Question 1b

Prepare a tabular summary of the dataset, indicating the data types (nominal, ordinal, interval or ratio) and relevant summary measures. (15 marks)

Question 1c

Employ visualization methods to create a dashboard that incorporates at least three graphical charts, each showing valuable insights from the dataset. Attach screenshots of every individual chart, along with the entire dashboard. Describe the steps for creating the charts and how the components of the dashboard collectively address the business problem identified in Question 1a. (Max word count: 250 words) (40 marks)

Question 2

Develop a proposal for a business analytics solution to tackle the business problem identified in Question 1a. It should include the discussion of at least two appropriate business analytics techniques, such as spreadsheet analysis, clustering, or predictive/prescriptive analytics. Explain how the relevant data fields can be used to generate useful information to address the business problem. (Max word count: 300 words) (30 marks)