Hypothesis Testing with T-Tests in Jamovi

Understanding group differences is a cornerstone of data analysis, but complex statistical software can feel overwhelming. Jamovi offers a powerful, intuitive interface to perform robust statistical tests without writing code. This text-based course guides you from statistical basics to confidently running and interpreting t-tests. You will learn how to set up your data, choose the correct test, verify statistical assumptions, and extract meaningful insights. What you will learn: 1. Understand the foundational concepts of hypothesis testing and when to use a t-test. 2. Conduct independent-samples, paired-samples, and one-sample t-tests in Jamovi. 3. Verify key statistical assumptions, including normality and homogeneity of variance. 4. Interpret and report p-values, confidence intervals, and effect sizes like Cohen's d. 5. Structure and clean your dataset within Jamovi for seamless analysis. You will begin with essential statistical terminology and the core logic behind t-tests. From there, you will progress through step-by-step written walkthroughs of each t-test type, complete with clear explanations of how to read Jamovi's output tables and report your findings. This course is designed for beginners, students, and researchers who are new to statistics or transitioning to Jamovi, requiring no prior programming or statistical experience. Start reading today to master group comparison analyses with confidence.