Design of Experiments
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Statistical designs are required for efficient experimentation in physical, chemical, biological, social and management sciences and in engineering. Some others topics focused upon in this course are analysis of variance, completely randomized and randomized block designs, Latin square designs, balanced incomplete block designs, factorial designs, confounding in blocks, fractional replications, orthogonal arrays, and response surface designs. Each topic is motivated by a real-life example.
This course also provides an accessible introduction to the study of matched sampling and other design techniques in any field (e.g., economics, education, epidemiology, medicine, Political science, etc.) conducting empirical research to evaluate the causal effects of interventions.
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