1. Chapter 7 Blocking and Confounding in the 2k Factorial Design

2. 7.2 Blocking a Replicated 2k Factorial Design
Blocking is a technique for dealing with controllable nuisance variables
A 2k factorial design with n replicates.
This is the same scenario discussed previously (Chapter 5, Section 5-6)
If there are n replicates of the design, then each replicate is a block
Each replicate is run in one of the blocks (time periods, batches of raw material, etc.)
Runs within the block are randomized

3. Example 7.1
Consider the example from Section 6-2; k = 2 factors, n = 3 replicates
This is the “usual” method for calculating a block sum of squares

4. The ANOVA table of Example 7.1

5. 7.3 Confounding in the 2k Factorial Design
Confounding is a design technique for arranging a complete factorial experiment in blocks, where block size is smaller than the number of treatment combinations in one replicate.
Cause information about certain treatment effects to be indistinguishable from (confounded with) blocks.
Consider the construction and analysis of the 2k factorial design in 2p incomplete blocks with p < k

6. 7.4 Confounding the 2k Factorial Design in Two Blocks
For example: Consider a 22 factorial design in 2 blocks.
Block 1: (1) and ab
Block 2: a and b
AB is confounded with blocks!
See Page 289
How to construct such designs??

7. Defining contrast:
xi is the level of the ith factor appearing in a particular treatment combination
i is the exponent appearing on the ith factor in the effect to be confounded
Treatment combinations that produce the same value of L (mod 2) will be placed in the same block.
See Page 290
Group:
Principal block

8. Estimation of error: See Page 292