Course Description

This course introduces participants to key concepts in descriptive statistics and probability, providing practical applications in health and business analytics. Participants will learn fundamental measures of data summarization, probability rules, conditional probability, and Bayesian inference. Hands-on coding sessions in R will reinforce theoretical concepts.

Learning Outcomes

• Understand and compute key measures of location and spread.
• Use graphical methods for data visualization.
• Apply fundamental probability concepts.
• Distinguish between independent and dependent events.
• Use Bayes’ Rule for probabilistic reasoning.
• Implement all concepts using R for real-world data analysis.

Course Structure and Content

Day	Topic
Day 1	Descriptive Statistics
Day 2	Probability
Day 3	Conditional Probability and Risk Analysis
Day 4	Bayesian Inference and Applications
Day 5	Further Applications in R

Teaching and Learning Strategy

• Lectures with real-world case studies.
• Hands-on coding 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 mini-project on real-world data analysis (50%)
• Successful candidates achieving 70% or more will be awarded a Certificate of Completion.

Certification and Career Opportunities

Upon completion, participants will receive a digital and printed certificate from GLOBALSTAT INTELLIGENCE SOLUTIONS. This course prepares learners for roles in data analytics, business intelligence, and health research.

Contact Information

Email: train@globalstatsol.com

Website: https://www.globalstatsol.com

Enrolling

Click below to enroll in this course.