Foundations of Statistics in Psychological Research

Understanding human behavior requires more than just observation—it demands rigorous data analysis to draw meaningful and reliable conclusions. This course guides you through the foundational statistical concepts necessary to read, design, and evaluate psychological research with confidence. You will transition from a statistics novice to a competent research reader, learning how to select the right analytical tests, interpret complex behavioral data, and understand the modern landscape of psychological science. What you'll learn: - Understand key terminology, foundational research designs, and the difference between descriptive and inferential statistics. - Apply core statistical tests, including t-tests, ANOVA, correlation, and regression, to behavioral datasets. - Interpret p-values, confidence intervals, and effect sizes to assess both the statistical and practical significance of research findings. - Evaluate published research papers critically by understanding statistical power, error types, and the context of the replication crisis. - Practice modern open-science workflows, including study preregistration and transparent data reporting guidelines. The course begins with foundational definitions and research design principles before moving step-by-step into hypothesis testing, specific statistical analyses, and modern scientific best practices. You will learn through clear, written explanations and practical examples designed for intuitive learning. This text-based course is designed entirely for beginners, making it ideal for undergraduate students, aspiring researchers, and professionals looking to build a strong foundation in behavioral statistics without any prior mathematical prerequisites. Start reading today to unlock the power of data in understanding human psychology.