Applied Biostatistics Course

Course Description

Welcome to the Applied Biostatistics course, an engaging and practical introduction to the world of medical statistical concepts and reasoning. This intermediate-level course is designed to equip you with the essential skills needed to analyze real-world medical data, providing you with a solid foundation in biostatistics and epidemiology.

Throughout this course, you'll dive into important topics in medical statistics, using examples from published clinical research papers to bring concepts to life. What sets this course apart is its hands-on approach – you'll have the opportunity to work with real-life datasets, giving you practical experience that's invaluable in the field.

We'll also introduce you to basic epidemiological concepts, covering various study designs and teaching you how to compute sample sizes. To make your learning experience smooth and accessible, we'll be using open-source, user-friendly software like R Commander and PS sample size software.

What You'll Learn

  • Important topics in medical statistical concepts and reasoning
  • Epidemiological study designs
  • Data analysis using R Commander
  • Basic statistical concepts, including descriptive statistics and hypothesis testing
  • How to select and apply appropriate statistical tests
  • Analysis of binary outcome data
  • Sample size computation and power analysis
  • Hands-on experience with real-life medical datasets

Who This Course Is For

  • Medical and healthcare professionals looking to enhance their data analysis skills
  • Researchers interested in improving their understanding of biostatistics
  • Students in health-related fields seeking practical experience with medical data analysis
  • Anyone interested in learning how to interpret and analyze medical research data

Real-World Applications

  • Designing and conducting medical research studies
  • Analyzing and interpreting clinical trial data
  • Evaluating the effectiveness of medical interventions
  • Making evidence-based decisions in healthcare settings
  • Contributing to public health policy development
  • Enhancing critical evaluation of published medical research
  • Improving patient care through data-driven insights

Syllabus

Week 1: Basic Statistical Concepts

  • Introduction to descriptive statistics and hypothesis testing
  • Data entry in statistical software
  • Introduction to R interface

Week 2: Basic Epidemiological Concepts

  • Study designs
  • Observational studies vs. randomized clinical trials

Week 3: Selecting Proper Statistical Tests

  • Scenarios defined by various data types
  • Decision-making process for test selection

Week 4: Comparing Means or Medians Between Two Groups

  • Student T-Test
  • Mann-Whitney U Test
  • Paired T-test
  • Wilcoxon Signed Rank Test

Week 5: Risk, Rate and Chi-Square Tests

  • Analysis of binary outcome data

Week 6: Sample Size and Power Analysis

  • Basic concepts in computing sample sizes
  • Estimation power for clinical studies

By the end of this course, you'll have a robust toolkit of biostatistical techniques and the confidence to apply them to real-world medical data. Don't miss this opportunity to enhance your analytical skills and contribute meaningfully to the field of medical research!