Science
A230 Data Analytics
Data Analytics equips students with a foundational understanding of data analysis, emphasising data collection techniques, statistical analysis, and data visualisation using tools like Microsoft Excel.
Key topics include data collection (sampling techniques, data extraction), data presentation (effective chart usage), probability (Bayes Theorem), and statistics fundamentals (central limit theorem, confidence intervals, hypothesis testing, regression, correlation). The module covers statistical models (t-test, chi-square, ANOVA) in Excel and introduces basic automation and AI for data sourcing. Students engage in hands-on data analysis and visualisation to derive insights for informed decision-making. The module aims to cultivate knowledge, skills and attitude in data processing, statistical reasoning, and visualisation, empowering students to make scientifically sound deductions from collected data and fostering a data-driven mindset.