Course Outline

Each day course will run from 9:30 AM to 5:00 PM with breaks for lunch and two coffee breaks.

Day One

🤝 Introductions and Welcome Address: We’ll begin our journey with warm introductions and a welcome speech, setting the stage for a collaborative and insightful learning experience.

🎤 Study Presentations by Attendees: Participants will engage in presenting their studies, offering a unique opportunity to share insights and foster mutual learning.

🔬 Understanding Reproducible Research: We will delve into the importance of reproducible research, a cornerstone of scientific integrity, focusing on methods that ensure consistency and reliability in results.

📊 Drafting Your Statistical Analysis Plan: To round off the day, we’ll start crafting a statistical analysis plan, a crucial step in structuring your research and analytical approach effectively.

🧹 Data Cleaning: Day two kicks off with a deep dive into the essentials of data cleaning and pivoting. Participants will learn the art of refining and restructuring data, which is crucial for accurate and insightful analysis.

This first day is designed to lay a solid foundation for the rest of the course. By focusing on both the theoretical and practical aspects of research and data analysis, attendees will gain a comprehensive understanding of reproducible research practices and the importance of a well-thought-out statistical analysis plan.

Day Two

🔍 Exploratory Data Analysis: Next, we’ll explore the techniques of exploratory data analysis. This session is designed to equip attendees with skills to uncover patterns, identify anomalies, and form hypotheses from complex data sets.

📊 Descriptive Data Analysis: The day concludes with a focus on descriptive data analysis. Here, attendees will master the skills to summarize and interpret data, providing meaningful insights into their studies and research.

📉 Regression Modelling: The final day begins with an in-depth session on regression modelling. Participants will delve into building and interpreting models to uncover relationships in their data, a critical skill for robust data analysis.

The second day of the course is structured to build upon the foundational knowledge from day one, with a focus on practical skills in data handling and analysis. Through hands-on coding with their own data, attendees will gain valuable experience in transforming their raw data into actionable insights.

Day Three

⏳ Survival Analysis: Following this, we will explore survival analysis. This segment will cover techniques for analyzing and predicting time-to-event data, an essential method in fields like healthcare and engineering.

🌈 Advanced Visualization: Next, we will cover advanced visualization techniques. This will empower participants to create compelling and informative visual representations of their data, enhancing the interpretability and impact of their research findings.

The third day is tailored to enhance participants’ skills in sophisticated data analysis and presentation. By the end of the third day you should be having a complete result section of your manuscript written up.