Introduction to Applied Statistics

3 credits · Graduate School

(Also listed as MATH 2821) Review of basic applied statistics. Development of the analysis of variance as a technique for interpreting experimental data. Generalized likelihood ratio principle, confounding, multiple comparisons, introduction to response surface methodology, and nonparameteric methods. Experimental design including: completely randomized, nested, orthogonal contrasts, randomized block, Latin squares, factorial, and fractional factorial. Prerequisite: 5820. [3]