DTS206TC Applied Linear Statistical Models - Coursework: Data Analysis with Linear Statistical Models using R
DTS206TC Applied Linear Statistical Models
School of AI and Advanced Computing
Coursework
23:59 31st May (Friday)
Data Analysis with Linear Statistical Models using R
Task.
For this coursework, you are required to choose a dataset of your own interest and per-
form a regression analysis using R. You will then write a short report documenting your
analysis and findings.
Report Requirements: The report should cover the following key aspects:
Criteria
Linear Regression
Table 1: Marking Criteria 1 (60 marks)
Marks Details
Data Analysis & Visualization
15
5 marks: Describe the chosen dataset and its variables of interest.
5 marks: Perform exploratory data analysis using appropriate R functions and packages.
5 marks: Visualize the data using plots, histograms, scatterplots, or other relevant graphical techniques.
5 marks: Conduct linear regression analysis using R.
5 marks: Specify the regression model and justify the choice of variables.
20
5 marks: Interpret the coefficients.
5 marks: Assess the goodness-of-fit of the model.
Diagnostics & Remedial Measures
15
5 marks: Perform diagnostic checks on the regression model to assess its validity.
5 marks: Identify any violations of the as- sumptions of linear regression.
5 marks: Implement appropriate remedial measures to address any issues identified.
Conclusion
5 marks: Summarize the key findings of the regression analysis.
10
5 marks: Discuss the implications of the results and any insights gained from the analysis.
Page 2/3
DTS206TC
AY 2023-2024
Criteria
Table 2: Marking Criteria 2 (40 marks)
Marks
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Clear and concise manner, with appropriate headings and subheadings. |
5 |
Clarity and organization of the report. 5 Quality and professionalism of the overall report. 5
The program runs correctly. 5
Originality 5 Reference 5
Note: for each item in the tables above, the work will be marked with the standard be- low:
• excellent = 5 marks
• good = 3 marks
• fair = 1 marks
• poor = 0 marks
Submission requirements.
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Only English solutions are accepted.
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Both report and codes should be submitted.
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File naming rule:
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– report: DTS206TC CW StudentID.pdf
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– code: DTS206TC CW StudentID.R
If multiple code files are to submit, create a code folder compresse it as .zip file, with the name of DTS206TC CW StudentID codes.zip
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File format
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– report : only .pdf is accepted.
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– code : .R
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– Data : Please do NOT include the data in the folder if the data is more than 80M. If you would like to share the data, please upload it to any e-Drive and paste the share link in the report (as reference or footnote).
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– Coverpage should be inserted in the report.
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Page limit: 10-30 pages
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The assignment must be submitted via Learning Mall Online to the correct drop box. Only electronic submission is accepted and no hard copy submission.
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Depth, accuracy and completeness of the regression analysis. |
5 |
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Include R code snippets to demonstrate their analy- sis and visualization techniques. |
5 |
