Null Hypothesis Significance Testing (NHST)
Learning Objectives
Upon completion of this comprehensive and engaging course, you will be able to:
- Compare and contrast the Fisher Framework vs. the Neyman-Pearson Framework for null hypothesis statistical testing
- Differentiate between a null hypothesis (H0) vs. an alternative hypothesis (H1)
- Differentiate between 1-tailed testing for a specific (directional) hypothesis vs. 2-tailed testing for an unspecific (non-directional) hypothesis
- Differentiate between a population distribution vs. a sampling distribution
- Conduct and interpret a single-case study z-test
- Conduct and interpret a one-sample z-test
- Conduct and interpret a one-sample t-test
- Explain the concepts of statistical significance, Type I errors, Type II errors, the p-value, α thresholds, and power
- Conduct a power analysis using G*Power (incl. for sample size planning)
Instructor
Christian Geiser, PhD is a former Professor of Quantitative Psychology with expertise in structural equation modeling, longitudinal data analysis, latent class modeling, multitrait-multimethod analysis, and psychometric methods. Dr. Geiser completed his doctoral training in quantitative psychology from Freie Universität Berlin in Germany, after which time he served as a faculty member at both Arizona State University as well as Utah State University, where he served as Principal Investigator on grants funded by the National Institutes of Health (NIH). In his academic career, he has published 75 peer-reviewed journal articles, 15 book chapters, and 5 books from leading publish houses such as Springer and Guilford Press. His work has been cited over 7,000 times, and he currently serves as an Editorial Board Member on Journal of Personality. Dr. Geiser provides statistical consultation services and serves as Director of Education for Quantfish, an online statistics training platform for health and social scientists.
9888 Windy Hollow Rd
