1. Chapter coverage Part A Part A –1: Practical tools –2: Consulting –3: Design Principles Part B (4-6) One-way ANOVA Part B (4-6) One-way ANOVA Part C (7-9) Factorial CRD Part C (7-9) Factorial CRD Part D (10-12) Unbalanced CRD Part D (10-12) Unbalanced CRD

2. Chapter coverage Part E (13-15) Questioning Assumptions Part E (13-15) Questioning Assumptions Part F (16-18) ANCOVA Part F (16-18) ANCOVA Part G (19-21) Random and Mixed Effects Part G (19-21) Random and Mixed Effects Part H: Nested and Split Plot Designs Part H: Nested and Split Plot Designs Part I: Repeated Measures and Cross- over Designs Part I: Repeated Measures and Cross- over Designs

3. Important Design Principles Replication Replication Randomization Randomization Blocking Blocking Multifactor Studies Multifactor Studies Confounding Confounding

4. Replication A repetition of the basic experiment A repetition of the basic experiment –Obtain estimate of experimental error –Increase power False replication False replication –Experimental Unit –Observational Unit

5. Randomization Random assignment of treatments to experimental units Random assignment of treatments to experimental units Random run order Random run order Random selection of experimental units from a population Random selection of experimental units from a population

6. Randomization Randomization restrictions Randomization restrictions –Stratification –Clustering

7. Restricted Randomization Restricted Randomization XXX XXX XXX

8. Systematic Sampling Easy to implement Easy to implement Possible loss of efficiency Possible loss of efficiency Beware systematic sources of variation Beware systematic sources of variation

9. Restricted Randomization Restricted Randomization XX XX XX XX XX XX

10. Stratification Inference on subgroups or strata Inference on subgroups or strata Greater precision (pooled variance) Greater precision (pooled variance)

11. Restricted Randomization Restricted Randomization XX XXX X XX XX XX

12. Clustering Convenient, Efficient (in terms of experimental effort) Convenient, Efficient (in terms of experimental effort) Possible loss of statistical efficiency Possible loss of statistical efficiency Important in adaptive sampling Important in adaptive sampling

13. Blocking Grouping to remove sources of heterogeneity Grouping to remove sources of heterogeneity Paired design is a form of blocking Paired design is a form of blocking

14. Multifactor Studies One at a time (OAT) designs One at a time (OAT) designs Multifactor designs Multifactor designs Orthogonality allows us to use multifactor designs to estimate factor effects and interactions Orthogonality allows us to use multifactor designs to estimate factor effects and interactions

15. Confounding Confusing factors in a design Confusing factors in a design –Good confounding –Bad confounding

16. Complete Confounding in a 2x2 table MF Trt 1N=4N=0 Trt 2N=0N=4

17. Confounding in a Randomized Complete Block Design (BxT is confounded with Error) Block 1Block 2…Block b T1T1 T1T1 …T1T1..…...…...…. TaTa TaTa …TaTa

18. Chapter 5--Completely Randomized Designs CRD Exercise CRD Exercise –Review 5.2,5.3,6.1-6.4 Class Class –5.1,5.4,5.5