Measures of Bivariate Association

Course Length: 1.5 Hours
Course Style: High-Definition On Demand Video

Learning Objectives

Upon completion of this comprehensive and engaging course, you will be able to:

  1. Compare and contrast the 5 key measures of bivariate association between continuous variables
  2. Compare and contrast the 4 key measures of bivariate association between ordinal variables
  3. Compare and contrast the 4 key measures of bivariate association between nominal variables
  4. Calculate the key measures of bivariate association by hand as well as in SPSS

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.

DISCLOSURES: This course can be classified as video-based homestudy without interactivity, and has an intended audience of professionals in the following sectors: Non-profit, Industry, University, Community College, Government Agency, Hospitals & Clinics, and Independent Researchers. Publication Academy, Inc. reports no conflicts of interest and has received no commercial support in the development and hosting of this training from its instructors. Publication Academy, Inc. maintains responsibility for this program and its contents. If you wish to enquire about a refund due to technical difficulties, please e-mail support@publicationacademy.org.

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