Data Analysis for Bioscientists: with Excel and R

Data analysis is fundamental to ensuring that research in Biosciences is rigorous, reliable, and applicable to real-world problems. It provides the quantitative framework that allows Bioscientists and healthcare professionals to make well-informed, data-driven decisions, ensuring that for example, medical advancements are safe, effective, and based on solid evidence. However, despite of its importance, many people find statistics and data analysis challenging for several reasons. For example, Statistics involves abstract concepts like probability, distributions, and statistical inference. These can be difficult to grasp, especially when they don't have clear, tangible examples in everyday life. Another reason is that statistics is often taught in a highly theoretical way, without much focus on practical, real-world applications. This can make it harder to see the relevance and importance of statistics, leading to disengagement. The aim of this book is therefore to help learners to overcome these difficulties by providing practical examples, encouraging active problem-solving, and emphasizing real-world applications of statistical analysis. Particular emphasis is placed on relevant examples; and how to address them using generally available software like Excel and R. The reader will be provided with detailed step-by-step instructions and screenshots, as well as with well-annotated R-snippets. To make the latter even more accessible, QR codes for these snippets are included in the book. The reader is encouraged to try out the R-snippets, and to modify them to their particular problems. Read more