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Analysis of Data from Designed Experiments |
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Augmented Design |
Example 2: [ Federer, W T (1956), Hawaiian Planter Record, 55, 191-208 and Federer, W T (1961), Biometrica, 19, 553-587 ] An experiment was conducted to compare the 8 new accessions with 4 check treatments to see whether any of the check treatment can be replaced by the new accession. The experiment was conducted using an augmented randomized complete block design with 3 blocks of size 7 (4 for check treatment and 3 for new accessions) for the first and third block and of size 6 (4 for check treatments and 2 for new accessions) for the second block such that each of 4 check treatments are allocated in block and the 8 new accessions are allotted randomly to remaining 20 experimental units of the three blocks. The final arrangement looks like:
|
Blocks |
Experimental
units |
||||||
|
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
|
1 |
N8(74) |
C3(78) |
C4(78) |
N3(70) |
C1(83) |
C2(77) |
N7(75) |
|
2 |
C4(91) |
C2(81) |
C1(79) |
C3(81) |
N1(79) |
N5(78) |
- |
|
3 |
N4(96) |
C3(87) |
C1(92) |
N2(89) |
C4(81) |
C2(79) |
N6(82) |
- Perform the
Analysis of variance to test the significance of
treatments (accession).
- Test the equality of check variety, accession and accessions with check effects.
- Compare
accessions with check varieties.
- Perform all
possible pairwise comparisons of check treatments with
each of the accessions and identify the best accession.
Analysis Using SAS Analysis Using SPSS Analysis Using SPAD
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Principal Component Analysis Cluster Analysis Groups of Experiments Non-Linear Models
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For
exposure on SAS, SPSS, MINITAB, SYSTAT and
MS-EXCEL
for analysis of data from designed experiments:
Please see Module I of Electronic Book II: Advances in Data Analytical Techniques
available at Design Resource Server (www.iasri.res.in/design)