Basic Inferential Statistics for Psychology

Understanding how to draw meaningful conclusions from behavioral data is a core skill for any psychology student or researcher. This text-only course guides you through the essential statistical methods used to analyze psychological studies, without requiring an advanced mathematical background. You will transition from simply reading research papers to truly understanding the statistical decisions behind them, learning how to choose, compute, and interpret the right tests for psychological data.\n\nWhat you'll learn:\n- Understand the core principles of hypothesis testing, statistical power, and significance levels.\n- Compare group means using independent and paired t-tests in psychological designs.\n- Analyze variance across multiple groups using ANOVA and post-hoc comparisons.\n- Measure relationships between behavioral variables using correlation and regression.\n- Interpret effect sizes and confidence intervals alongside p-values for modern, robust research.\n- Practice selecting the appropriate statistical test based on your research questions and data types.\n\nStarting with fundamental definitions of populations, samples, and probability, the course takes you step-by-step through parametric and non-parametric tests, explaining the logic behind each statistical decision. Designed specifically for beginners, this course requires no prior statistical or programming experience.\n\nStart reading today to master the quantitative side of psychological science.