Module 1: Understanding Data

Module 1: Understanding Data

This module provides a foundational understanding of how to analyse and interpret data to make better decisions in sports science and analytics. Benjamin will emphasise the practical applications of data analysis in a sports science context.

Throughout the lessons, you will gain valuable insights into:

• The importance of understanding data metrics and how they empower informed decision-making while avoiding common pitfalls in interpretation.
• Differentiating between types of data (qualitative vs. quantitative) and understanding the significance of interval and ratio scales.
• Effective methods for collecting and cleaning data, including identifying outliers, handling missing data, and ensuring dataset reliability.
• Key statistical tools and principles such as measures of central tendency, dispersion, accuracy, validity, and reliability to assess data quality.
• Advanced statistical concepts like Intraclass Correlation Coefficient (ICC), P-values, and confidence intervals to deepen your analytical skills.

Upon completing this course, you will have a general understanding of how to work with data, tailor analyses to key objectives, and apply these insights to drive performance and success in your practice.