Correlations and T-Tests for Healthcare Data Analysis

Understanding the relationships within healthcare data is crucial for informed decision-making. Gain the foundational statistical skills to interpret and compare healthcare data effectively. This course will equip you with the ability to confidently apply correlation and t-test analyses, transforming raw healthcare numbers into actionable insights for clinical or research settings. What you'll learn: Understand the fundamental concepts of statistical inference and hypothesis testing. Learn how to calculate and interpret various correlation coefficients to measure relationships in data. Apply independent and paired sample t-tests to compare means between two groups. Conduct basic ANOVA (Analysis of Variance) for comparing means across multiple groups. Evaluate the assumptions underlying these statistical tests to ensure valid and reliable results. Understand the importance of effect size and confidence intervals for robust interpretation. Practice interpreting statistical output to draw meaningful conclusions from healthcare datasets. The course begins with essential statistical concepts and data types, then progressively introduces correlations, t-tests, and ANOVA, concluding with practical application and interpretation exercises. This course is designed for absolute beginners in statistics, particularly those interested in healthcare, clinical research, or public health, with no prior statistical knowledge required. Start your journey to becoming a confident healthcare data analyst today.