ANL203: (Analytics for Decision-Making) You are to follow the Six-Stage Problem-Solving Process to answer the following questions using this dataset.

Module / Subject / School:

ANL203: Analytics for Decision-Making

Singapore University of Social Sciences (SUSS)

Requirements: 

Question 1

“Employment_GBA.csv” records the Graduate Employment Survey (GES), a collaborative effort among NTU, NUS, SMU, SIT (since 2014), SUTD (since 2015), and SUSS (since 2018) to conduct an annual survey of graduate employment conditions approximately six months after their final examinations.

The Ministry of Education (MOE) publishes the results of key employment indicators from this survey to provide prospective students with timely and comparable data, enabling them to make informed decisions about their courses. Graduates from NTU, NUS, SMU, and SUSS are surveyed in November.

However, due to differences in academic calendars, graduates from SUTD and SIT are surveyed in February and March, respectively. You are to follow the Six-Stage Problem-Solving Process to answer the following questions using this dataset.

(a) Identify one (1) possible problem that can be addressed by analysing the dataset and discuss the critical assumptions for potential analytics application. (Up to 150 words for part (a))

(15 marks)

(b) Prepare a summary of the dataset in tabular format. It should contain the data dictionary, each data field’s type and summary measures. (Up to 150 words for part (b))

(15 marks)

(c) Develop a proposal for an analytics solution. It should contain a discussion of the appropriateness of at least one (1) business analytics techniques to use and the explanation of how the technique(s) can be used to address the identified problem in part a). You are only required to discuss the expected results and do not need to construct the actual model(s). (Use up to 250 words for part (c))

(30 marks)

(d) Employ data visualisation techniques to develop four (4) charts to show an interesting trend, pattern, or relationship among variables from the dataset. Provide a screenshot of each produced chart. Explain how the charts are created and discuss why the charts are recommended. (Use up to 250 words for part (d))

(20 marks)

• Your group shall submit original work. Do not copy any content of your submission from any source (regardless of public or private). The GBA submission should not exceed 1000 words. The word count does not include the Appendix (maximum 3 pages).

• The quality of your report is paramount. Marks will be deducted for poor report writing skills such as poor command of English, poor paraphrasing, lacking clarity, etc. 20 marks will be allocated to professional presentation and writing of your GBA report, e.g., covering the following aspects,

• Organisation
• Communication of ideas
• Citation and reference
• Grammar

What we score:

78%

Our Writer’s Comment 

This assignment is designed to assess students’ understanding of business practices.

To secure an A+ grade, adhere to these guidelines and make sure your work aligns with the grading criteria:

Part (a): Identify a Problem and Assumptions (15 marks)

Here, you’re asked to identify a specific problem from the dataset. The key is to be very clear about the problem you’re solving and why it’s important. Think of problems like unemployment rates varying by university or differences in salary outcomes by degree.

Tip: Make sure to mention the critical assumptions. For example, you might assume that all universities collect data in the same way, or that employment outcomes are not significantly influenced by external economic factors. Keep it concise, but show you’ve thought critically about the data.

How to Improve: Be specific. Instead of saying, “We will analyze employment rates,” say, “We aim to analyze the impact of different graduation periods on employment outcomes, assuming consistent job market conditions.”

Part (b): Summarize the Dataset (15 marks)

In this section, you need to provide a clean and well-organized summary of the dataset. Create a data dictionary that clearly defines each variable, its type (e.g., numeric, categorical), and key summary measures (like mean, median, etc.).

Tip: Make sure to organize the summary in a way that’s easy to read. Use a table format with columns like Variable Name, Data Type, Summary Statistics (Mean, Median, etc.). Also, don’t forget to provide accurate measures like standard deviations where relevant.

How to Improve: The more precise your summary is, the better. If your dataset includes salary information, include ranges (e.g., min, max) to show you understand the data variability.

Part (c): Proposal for an Analytics Solution (30 marks)

This part is all about proposing a method that makes sense. Choose an analytics technique like regression analysis or clustering. The key is to explain why it’s suitable for the problem in Part (a).

For example, if you’re analyzing employment rates, regression can help you understand how factors like university or degree type influence job outcomes. You don’t have to build the actual model—just explain what the model would do and what kind of insights it could reveal.

Tip: Be sure to link your chosen technique directly to the problem. Show how the expected results (e.g., coefficients in a regression model) would help solve or explain the issue you’ve identified.

How to Improve: Make sure your explanation is focused. Rather than giving too many technical details, focus on how the technique provides actionable insights for decision-making.

Part (d): Data Visualisation (20 marks)

This section requires you to create four charts. The goal is to find trends or patterns that are meaningful, such as salary trends across universities or the employment rate over time.

When selecting charts:

• Line charts can show trends over time.
• Bar charts can compare variables like average salary across universities.
• Scatter plots can show relationships, like between GPA and employment rates.
• Pie charts can highlight distributions, such as employment sectors.

Tip: Explain why each chart is effective. For instance, if you use a line chart, say something like, “This line chart shows the upward trend in employment rates for NTU graduates over five years, highlighting a positive impact of university initiatives.”

How to Improve: Don’t just describe the charts—analyze what they show. The more insights you extract from the charts, the stronger your analysis will be.

Professional Presentation (20 marks)

You’ll lose marks if your report isn’t well-organized or clearly written.

Tip: Make sure your report flows logically, with a clear introduction, body, and conclusion. Use headings and subheadings to organize content. Avoid grammar mistakes and be clear with your explanations. Citing sources properly also contributes to a professional presentation.

How to Improve: Proofread carefully, and maybe even ask a peer to review it. Ensure that your ideas are communicated effectively and that the entire report feels cohesive.

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