Course Description

This 15-day course provides an in-depth understanding of epidemiologic study designs, statistical techniques for analyzing epidemiologic data, and hands-on applications using R. Topics include risk assessment, stratified analysis, regression models, survival analysis, and handling missing data.

Learning Outcomes

• Understand study designs and their applications.
• Compute measures of effect for categorical and person-time data.
• Perform logistic regression and extensions.
• Analyze survival data using Kaplan-Meier estimators and Cox models.
• Conduct power and sample size estimation for epidemiologic studies.
• Apply all methods using R for real-world epidemiologic research.

Course Structure and Content

Day	Topic
Day 1-2	Introduction & Study Design
Day 3-4	Measures of Effect & Attributable Risk
Day 5-6	Confounding, Standardization & Stratified Categorical Data
Day 7-8	Logistic Regression & Extensions
Day 9-10	Meta-Analysis, Equivalence Studies & Cross-Over Design
Day 11-12	Survival Analysis & Proportional Hazards Model
Day 13-15	Practical Applications with R

Teaching and Learning Strategy

• Lectures with real-world epidemiologic examples.
• Hands-on statistical computing exercises in R.
• Group discussions and problem-solving activities.
• Self-paced learning through additional resources.

Assessment Strategy

• Practical coding exercises (30%)
• Conceptual quizzes (20%)
• A final project on epidemiologic data analysis (50%)
• 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. The course prepares learners for careers in epidemiologic research, public health analysis, and biostatistical consulting.

Contact Information

Email: train@globalstatsol.com

Website: https://www.globalstatsol.com

Enrolling

Click below to enroll in this course.