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Chapter coverage. Part A 1: Practical tools 2: Consulting 3: Design Principles Part B (4-6) One-way ANOVA Part C (7-9) Factorial CRD Part D (10-12) Unbalanced CRD. Chapter coverage. Part E (13-15) Questioning Assumptions Part F (16-18) ANCOVA Part G (19-21) Random and Mixed Effects
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Chapter coverage • Part A • 1: Practical tools • 2: Consulting • 3: Design Principles • Part B (4-6) One-way ANOVA • Part C (7-9) Factorial CRD • Part D (10-12) Unbalanced CRD
Chapter coverage • Part E (13-15) Questioning Assumptions • Part F (16-18) ANCOVA • Part G (19-21) Random and Mixed Effects • Part H: Nested and Split Plot Designs • Part I: Repeated Measures and Cross-over Designs
Important Design Principles • Replication • Randomization • Blocking • Multifactor Studies • Confounding
Replication • A repetition of the basic experiment • Obtain estimate of experimental error • Increase power • False replication • Experimental Unit • Observational Unit
Randomization • Random assignment of treatments to experimental units • Random run order • Random selection of experimental units from a population
Randomization • Randomization restrictions • Stratification • Clustering
Systematic Sampling • Easy to implement • Possible loss of efficiency • Beware systematic sources of variation
Stratification • Inference on subgroups or strata • Greater precision (pooled variance)
Clustering • Convenient, Efficient (in terms of experimental effort) • Possible loss of statistical efficiency • Important in adaptive sampling
Blocking • Grouping to remove sources of heterogeneity • Paired design is a form of blocking
Multifactor Studies • One at a time (OAT) designs • Multifactor designs • Orthogonality allows us to use multifactor designs to estimate factor effects and interactions
Confounding • Confusing factors in a design • Good confounding • Bad confounding
Confounding in a Randomized Complete Block Design (BxT is confounded with Error)
Chapter 5--Completely Randomized Designs • CRD Exercise • Review 5.2,5.3,6.1-6.4 • Class • 5.1,5.4,5.5