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Statistical Data Projects Linked to SDGs


                  Data visualisation is the process of transforming raw data into visual formats such as graphs,

                  charts, and infographics, making complex datasets more accessible and easier to understand.
                  By presenting data in a visual form, it allows patterns, trends, and relationships to emerge
                  clearly, which might be difficult to identify from raw, unprocessed numbers alone. Visualisation
                  techniques help to reveal insights that can drive decision-making, offer a deeper understanding

                  of the subject matter, and highlight areas that require attention.
                  Moreover, data visualisation enhances the ability to tell a compelling story with data, turning
                  abstract figures into something tangible and relatable. It allows users to interact with the data,

                  enabling them to explore different perspectives and drill down into the details. This makes it
                  easier for individuals and organisations to identify correlations, anomalies, and key insights
                  that are pivotal for strategy development, forecasting, and problem-solving.

                  For Example: Company X made a profit of
                  10 million in Year 2023 and 15 million in
                  Year 2024.

                  Let’s  explore  how  statistical  data  linked
                  to the SDGs and their data visualisation
                  can be understood through the given

                  scenarios.
                  Scenario 1: Data Visualisation of AI for Life Forms

                  A group of students is tasked with using the provided Biodiversity Trends Data to understand
                  how AI can help track and predict the population growth of endangered species over time.
                  The students will analyse the data, which contains the population trends of tigers, pandas, and

                  rhinos over five years (from 2010 to 2030).
                  The purpose of this scenario is as follows:

                  The goal of this task is to help students learn how AI technologies can be used to monitor
                  biodiversity, track the population changes of endangered species, and forecast future trends
                  using historical data. Students will explore how AI models can predict the growth of these

                  species and how they can be used for conservation efforts.
                  Sample data is as follows:















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