Supported by real-world case studies, this essential textbook provides a detailed overview of the use of biostatistical tools and methods, enabling students and researchers to undertake their own research with confidence and understanding.After a general introduction to the field, the book provides a step-by-step description of the essential statistical methods that are foundational to analysing data from clinical trials, epidemiological studies and other health-related research. From basic concepts such as probability and distribution through to hypothesis testing, regression analysis, survival analysis, meta-analysis and systematic reviews, each chapter is designed with a clear pedagogical approach featuring explanatory diagrams, real-life examples and sample problems. Later sections of the book cover clinical trial design and analysis, diagnostic testing, Bayesian methods and machine learning. Through this detailed, comprehensive treatment of the key tools and methods, the book encourages readers to develop their own critical thinking skills, recognising good or bad pieces of research when they see them, asking questions about where evidence and assumptions come from or choosing the most appropriate biostatistical methodologies in their own research.Written by a team of experts with extensive teaching experience in this field, this is the ideal textbook for graduate students and researchers across the biomedical sciences, from public health to epidemiology to clinical medicine.

Supported by real-world case studies, this essential textbook provides a detailed overview of the use of biostatistical tools and methods, enabling students and researchers to undertake their own research with confidence and understanding.After a general introduction to the field, the book provides a step-by-step description of the essential statistical methods that are foundational to analysing data from clinical trials, epidemiological studies and other health-related research. From basic concepts such as probability and distribution through to hypothesis testing, regression analysis, survival analysis, meta-analysis and systematic reviews, each chapter is designed with a clear pedagogical approach featuring explanatory diagrams, real-life examples and sample problems. Later sections of the book cover clinical trial design and analysis, diagnostic testing, Bayesian methods and machine learning. Through this detailed, comprehensive treatment of the key tools and methods, the book encourages readers to develop their own critical thinking skills, recognising good or bad pieces of research when they see them, asking questions about where evidence and assumptions come from or choosing the most appropriate biostatistical methodologies in their own research.Written by a team of experts with extensive teaching experience in this field, this is the ideal textbook for graduate students and researchers across the biomedical sciences, from public health to epidemiology to clinical medicine.