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Direct linkLübke, Karsten; Gehrke, Matthias; Horst, Jörg; Szepannek, Gero – Journal of Statistics Education, 2020
Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…
Descriptors: Inferences, Simulation, Attribution Theory, Teaching Methods
Ann M. Brearley; Kollin W. Rott; Laura J. Le – Journal of Statistics and Data Science Education, 2023
We present a unique and innovative course, Biostatistical Literacy, developed at the University of Minnesota. The course is aimed at public health graduate students and health sciences professionals. Its goal is to develop students' ability to read and interpret statistical results in the medical and public health literature. The content spans the…
Descriptors: Statistics Education, Data Interpretation, Teaching Methods, Biology
Sole, Marla A. – Mathematics Teacher, 2016
Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…
Descriptors: Statistics, Mathematics Instruction, Data Collection, Teaching Methods
