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Presented by:
Hossein Ahmadi
Behzad Hosseinzadeh
Supervisor: Dr.Riahi
DESIGN OF EXPERIMENTS
NESTED DESIGNS
Spring 2015 numbers of slides: 19
2
Definition
Nested design is a research design in which
levels of one factor (say, Factor B ) are
hierarchically subsumed under (or nested
within) levels of another factor (say, Factor A ).
As a result, assessing the complete combination
of A and B levels is not possible in a nested
design.
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
3
Nested Vs. Crossed
Factors A and B are considered crossed if
Every level of B occurs with every level of A
A factorial model involves crossed factors
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
4
Nested Vs. Crossed
Factors A and B considered nested if:
Levels of B occur with only one level of A
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
5
Example
For example, consider a typical
provenance study where a forest
geneticist collects 5 seeds from 5
superior trees in each of 3 forests. The
seeds are germinated in a greenhouse
and the seedlings are
measured for height
growth. Graphically,
the design would look
like this...
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
6
Example
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
7
Linear Model
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
8
Null Hypotheses
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
9
Null Hypotheses
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
10
Partitioning Total Variation
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
11
Nested ANOVA Table
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
12
Testing Null Hypotheses
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
13
Computation
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
14
Computation
A B C D E Forest
1 2 3 4 5 6 7 8 9 10 Tree
15.8 13.9 18.5 17.9 12.3 14 19.5 18.7 16 15.8
Rep15.6 14.2 18 18.1 13 13.1 17.5 19 15.7 15.6
16 13.5 18.4 17.4 12.7 13.5 19.1 18.8 16.1 16.3
15.8 13.87 18.3 17.8 12.67 13.54 18.7 18.83 15.93 15.9
14.83 18.05 13.1 18.77 15.93
16.13
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
15
Computation
SSA = 2 x 3 [(16.13-14.83)2
+ (16.13-18.05)2
+ (16.13-13.1)2
+ (16.13-18.77)2
+ (16.13-15.93)2
]
= 129.28
SS(A)B = 3 [(15.8-14.83)2
+ (13.87-14.83)2
+ (18.3-18.05)2
+
(17.8-18.05)2
+ (12.67-13.1)2
+ (13.54-13.1)2
+
(18.7-18.77)2
+ (18.83-18.77)2
+ (15.93-15.93)2
+
(15.9-15.93)2
]
= 7.4
SSWerror = 4.01
TSS = 140.69
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
16
Computation
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation
17
Computation
- Definition
- Nested
Vs. Crossed
- Example
- Linear Model
- Effects
- Null
Hypotheses
- Partitioning
Total Variation
- Nested ANOVA
Table
- Testing Null
Hypotheses
- Computation

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Nested Designs Slides

  • 1. Presented by: Hossein Ahmadi Behzad Hosseinzadeh Supervisor: Dr.Riahi DESIGN OF EXPERIMENTS NESTED DESIGNS Spring 2015 numbers of slides: 19
  • 2. 2 Definition Nested design is a research design in which levels of one factor (say, Factor B ) are hierarchically subsumed under (or nested within) levels of another factor (say, Factor A ). As a result, assessing the complete combination of A and B levels is not possible in a nested design. - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 3. 3 Nested Vs. Crossed Factors A and B are considered crossed if Every level of B occurs with every level of A A factorial model involves crossed factors - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 4. 4 Nested Vs. Crossed Factors A and B considered nested if: Levels of B occur with only one level of A - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 5. 5 Example For example, consider a typical provenance study where a forest geneticist collects 5 seeds from 5 superior trees in each of 3 forests. The seeds are germinated in a greenhouse and the seedlings are measured for height growth. Graphically, the design would look like this... - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 6. 6 Example - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 7. 7 Linear Model - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 8. 8 Null Hypotheses - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 9. 9 Null Hypotheses - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 10. 10 Partitioning Total Variation - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 11. 11 Nested ANOVA Table - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 12. 12 Testing Null Hypotheses - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 13. 13 Computation - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 14. 14 Computation A B C D E Forest 1 2 3 4 5 6 7 8 9 10 Tree 15.8 13.9 18.5 17.9 12.3 14 19.5 18.7 16 15.8 Rep15.6 14.2 18 18.1 13 13.1 17.5 19 15.7 15.6 16 13.5 18.4 17.4 12.7 13.5 19.1 18.8 16.1 16.3 15.8 13.87 18.3 17.8 12.67 13.54 18.7 18.83 15.93 15.9 14.83 18.05 13.1 18.77 15.93 16.13 - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 15. 15 Computation SSA = 2 x 3 [(16.13-14.83)2 + (16.13-18.05)2 + (16.13-13.1)2 + (16.13-18.77)2 + (16.13-15.93)2 ] = 129.28 SS(A)B = 3 [(15.8-14.83)2 + (13.87-14.83)2 + (18.3-18.05)2 + (17.8-18.05)2 + (12.67-13.1)2 + (13.54-13.1)2 + (18.7-18.77)2 + (18.83-18.77)2 + (15.93-15.93)2 + (15.9-15.93)2 ] = 7.4 SSWerror = 4.01 TSS = 140.69 - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 16. 16 Computation - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation
  • 17. 17 Computation - Definition - Nested Vs. Crossed - Example - Linear Model - Effects - Null Hypotheses - Partitioning Total Variation - Nested ANOVA Table - Testing Null Hypotheses - Computation