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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
Dunn, Peter K. – Journal of Statistics Education, 2013
In this paper, we report a case study that illustrates the importance in interpreting the results from statistical tests, and shows the difference between practical importance and statistical significance. This case study presents three sets of data concerning the performance of two brands of batteries. The data are easy to describe and…
Descriptors: Equipment, Performance, Statistical Analysis, Statistical Significance
