ESE1008 Global Environmental Trends Assignment Report: Data Analysis & Climate Insights

Published: 04 Aug, 2025
Category Assignment Subject Computer Science
University Temasek Polytechnic Module Title ESE1008 Data Visualisation and Analytics
Assessment Type Report

Project Title: Global Environmental Trends

Background:

The Global Environmental Trends dataset provides insights into global climate dynamics, including temperature trends, carbon emissions, sea-level changes, rainfall variability, renewable energy usage, extreme weather events, and forest coverage. This dataset serves as an essential tool for researchers, policymakers, environmental scientists, and educators studying environmental changes and sustainability.

Analysing this dataset can enhance understanding of global warming impacts, help model future environmental scenarios and inform strategies for sustainability and climate change mitigation.

Examples of investigative questions include:

  • How does the increase in global average temperatures correlate with rising sea levels?
  • Is there a clear relationship between CO2 emissions per capita and renewable energy adoption across regions?

Refer to Table 1 for the explanation of the features/variables.

Note: The data provided has been modified and re-generated for educational purposes to simulate meaningful trends with controlled randomness.

Objectives:

The objectives of this project are as follows:

Data Cleaning: To perform data cleaning to prepare the dataset for further analysis.

Exploratory Data Analysis (EDA): To conduct exploratory data analysis to gain statistical insights into the dataset. Key activities include gathering statistical summaries, plotting box plots and histograms for numerical variables, and creating visual charts for categorical data types. A correlation matrix for all numerical variables should also be included.

Formulating Investigative Questions or Hypotheses: To propose preliminary investigative questions or hypotheses based on the dataset. Use data visualisation techniques to explore and answer these questions or hypotheses. Go beyond the initial findings to explore specific scenarios in more depth, uncovering additional insights.

Data Transformation: To perform data transformations based on insights gained from the EDA. This may include outlier removal and aggregation to improve data quality.

Model Selection and Evaluation

Employ Linear Regression to predict Average Temperatures

Employ Logistic Regression to classify Carbon Emissions. Create a new target variable Carbon_Emission_Level (i.e. for CO2_Emissions_tons_per_capita higher than the mean, define it as “high_co2”, else, define it as “low_co2”). Model the probability of the likelihood of a country's likely to be of high carbon emission level based on predictors like average temperature, sea level, renewable energy, rainfall, etc. (Hint: You may need to normalise the variables). Evaluate model accuracy and interpret results comprehensively.

Additional Notes:

Complete Objectives 1, 2, and 3, compiling findings into Report 1, which should be no more than 20 pages.

For Objective 2, analyse all variables in the dataset and provide evidence of your work in both Knime and Tableau. In the report, show the statistic table, include any two box plots, two histograms, and two pie charts which are worth mentioning, plus the linear co-relation matrix.

It is not necessary to answer the preliminary investigative questions in Report 1; answer them in Report 2. You may use AI tools to help generate relevant questions if needed. Propose at least two two-variable and three three-variable (further Insights) questions for Objective 3, ensuring they are unique from those in the introduction. A total of five investigative questions:

  • Two questions that examine the relationship between two variables (e.g., “Does a country’s population size correlate with its CO2_Emissions_tons_per_capita over the years?”).
  • Three questions that involve three variables (e.g., “How do Sea_Level_Rise_mm, Rainfall_mm, and Extreme_Weather_Events collectively influence Avg_Temperature_degC in different countries?”).

For Report 2, perform the necessary data transformations following your EDA and use the data to address the investigative questions. Copy both the investigative questions from the Background section and the proposed questions from Report 1, and provide answers for each one. Additionally, include Linear and Logistic Regression model analysis and conclude with a reflection.

Reflection: In your reflection, evaluate the dataset’s usefulness, model accuracy, and any feature enhancements (such as additional features) that could improve the model’s predictive accuracy. Keep Report 2 to a maximum of 20 pages.

Data Dictionary (variable descriptions)

Column Description
Year Year of recorded data
Country Name of the country or region
Avg_Temperature_degC Average temperature in degrees Celsius
CO2_Emissions_tons_per_capita Carbon dioxide emissions measured per capita in tons
Sea_Level_Rise_mm Measured sea level rise in millimeters
Rainfall_mm Total rainfall measured in millimeters
Population Total population of the country or region
Renewable_Energy_pct Percentage of energy derived from renewable sources
Extreme_Weather_Events Number of recorded extreme weather events
Forest_Area_pct Percentage of total land area covered by forests

Table 1

Data Assigned:

S/N Data File Assigned (Tick)
1 global_env_1.csv
2 global_env_2.csv
3 global_env_3.csv
4 global_env_4.csv
5 global_env_5.csv

Need Plagiarism free Answers for your college/ university Assignments

 Order Non Plagiarized Assignment

If you are stressed about the coursework on CU6027 Digital Marketing, then there is no need to worry now! Whether you need Computer Science Assignment Help or Marketing Assignment Help, you will get expert guidance and help on report writing services, which will make your concepts strong. We also provide you with free assignment solutions that will help you in understanding. And the best part? All the content is 100% original, written by PhD expert writers, and is well-researched so that you get the best quality. So don't delay now, boost your grades with our help!

Workingment Unique Features

Hire Assignment Helper Today!


Latest Free Samples for University Students

RBP020L063H Leadership and Change Management Assignment Sample

Category: Assignment

Subject: Management

University: University of Roehampton

Module Title: RBP020L063H Leadership and Change Management

View Free Samples

HRMM080 Ethical and Responsible Leadership AS2 Reflective Portfolio Sample

Category: Assignment

Subject: Management

University: University of Northampton

Module Title: HRMM080 Ethical and Responsible Leadership

View Free Samples

ACAD1346 The child’s live Experience Developing Confidence Learners Assignment Sample

Category: Assignment

Subject: Education

University: University of Greenwich (UOG)

Module Title: ACAD1346 The child’s live Experience Developing Confidence Learners

View Free Samples

NUR7011 Developing Healthcare Leaders Assignment Sample | BPP

Category: Assignment

Subject: Nursing

University: BPP University

Module Title: NUR7011 Developing Healthcare Leaders

View Free Samples

Project Management, Leadership and Skills: Planning & Control Portfolio Example

Category: Assignment

Subject: Management

University: University of Salford Manchester

Module Title: Project Management, Leadership and Skills: Planning & Control

View Free Samples
Online Assignment Help in UK