Course Description

This 10-day course focuses on applying medical statistics in R to real-world health and disease-related studies. The course covers a wide range of topics, from clinical trials to survival analysis and epidemiological studies, giving participants the tools to analyze health data efficiently and make evidence-based decisions in medical research.

Learning Outcomes

• Understand and apply statistical methods for analyzing medical data in R.
• Learn to design and analyze clinical trials, including randomization and blinding.
• Conduct survival analysis and interpret Kaplan-Meier curves and Cox regression models.
• Use epidemiological methods to analyze cohort and case-control studies.
• Analyze categorical data in medical studies, including chi-square tests and logistic regression.
• Perform statistical modeling for longitudinal data and repeated measures.
• Implement all methods in R, using relevant packages and visualizations for medical statistics.

Course Structure and Content

Day	Topic
Day 1	Introduction to Medical Statistics & R: Data Handling and Visualization
Day 2	Clinical Trials: Study Design, Randomization, and Blinding
Day 3	Descriptive Statistics in Medical Data: Measures of Central Tendency and Dispersion
Day 4	Hypothesis Testing in Medical Studies: t-tests, ANOVA, and Nonparametric Tests
Day 5	Chi-Square Tests and Logistic Regression for Categorical Data
Day 6	Survival Analysis: Kaplan-Meier Estimation and Log-Rank Test
Day 7	Cox Proportional Hazards Model and Interpretation
Day 8	Longitudinal Data Analysis: Mixed-Effects Models for Repeated Measures
Day 9	Epidemiological Methods: Cohort and Case-Control Studies
Day 10	Practical Applications in R: Analyzing Medical Data with R

Teaching and Learning Strategy

• Lectures with a focus on real-world applications in medical research.
• Hands-on R programming exercises for data analysis, modeling, and visualization.
• Case studies based on clinical trials, survival analysis, and epidemiological studies.
• Group discussions and collaborative problem-solving.

Assessment Strategy

• Practical exercises in analyzing medical data and implementing statistical models (40%)
• Conceptual quizzes to test knowledge of medical statistics and methods (20%)
• Final project involving the analysis of a real-world medical dataset (40%)
• Participants scoring 70% or above will receive a Certificate of Completion.

Certification and Career Opportunities

Upon completion, participants will receive a digital and printed certificate from GLOBALSTAT INTELLIGENCE SOLUTIONS. This course will benefit professionals working in healthcare, epidemiology, clinical research, and biostatistics, helping them develop the skills necessary for data analysis and statistical modeling in health studies.

Contact Information

Email: train@globalstatsol.com

Website: https://www.globalstatsol.com

Enrolling

Click below to enroll in this course.