Quantitative Methods Designing experiments - keeping it simple.

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Presentation transcript:

Quantitative Methods Designing experiments - keeping it simple

Three principles of experimental design Replication Randomisation Blocking

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design Design and analysis ReplicationDegrees of freedom

Designing experiments - keeping it simple Three principles of experimental design Replication Randomisation Blocking

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design UnitTrRandTr 1A 2A 3A 4A 5B 6B 7B 8B 9C 10C 11C 12C 13D 14D 15D 16D sample 16 Tr RandTr

Designing experiments - keeping it simple Three principles of experimental design UnitTrRandTr 1AC 2AB 3AD 4AB 5BB 6BA 7BD 8BA 9CD 10CB 11CA 12CC 13DC 14DD 15DC 16DA sample 16 Tr RandTr

Designing experiments - keeping it simple Three principles of experimental design Design and analysis Replication Randomisation Degrees of freedom Valid estimate of EMS

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design Design and analysis Replication Randomisation Degrees of freedom Valid estimate of EMS

Designing experiments - keeping it simple Three principles of experimental design Replication Randomisation Blocking

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design

Designing experiments - keeping it simple Three principles of experimental design Design and analysis Replication Randomisation Blocking Degrees of freedom Valid estimate of EMS Elimination

Designing experiments - keeping it simple Fitted values and models

Designing experiments - keeping it simple Fitted values and models

Term Coef Constant BLOCK BEAN Designing experiments - keeping it simple Fitted values and models

Term Coef Constant BLOCK BEAN Designing experiments - keeping it simple Fitted values and models

Term Coef Constant BLOCK BEAN BLOCK Designing experiments - keeping it simple Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple So the fitted value for a plot in Block 2 planted with bean variety 6 is Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple So the fitted value for a plot in Block 2 planted with bean variety 6 is Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple So the fitted value for a plot in Block 2 planted with bean variety 6 is Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple So the fitted value for a plot in Block 2 planted with bean variety 6 is ( ) Fitted values and models

Term Coef Constant BLOCK BEAN BEAN BLOCK Designing experiments - keeping it simple So the fitted value for a plot in Block 2 planted with bean variety 6 is ( ) = Fitted values and models

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Orthogonality

Designing experiments - keeping it simple Design and analysis Replication Randomisation Blocking Orthogonality Degrees of freedom Valid estimate of EMS Elimination Seq=Adj SS Orthogonality

Designing experiments - keeping it simple Next week: Combining continuous and categorical variables Read Chapter 6 Experiments should be designed and not just happen Think about reducing error variation and –replication: enough separate datapoints –randomisation: avoid bias and give separateness –blocking: managing the unavoidable error variation The statistical ideas we’ve been learning so far in the course help us to understand experimental design and analysis Last words…