Analysis of Data from Designed Experiments

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	Analysis of Data from Designed Experiments
	Analysis of Covariance

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Example: {Gomez, K.A. and Gomez, A.A., 1984, Statistical Procedures for Agricultural Research, 2^nd Edition, John Wiley and Sons, New York, pp437-448}. A trial was designed to evaluate 15 rice varieties grown in soil with a toxic level of iron. The experiment was in a RCB design with three replications. Guard rows of a susceptible check variety were planted on two sides of each experimental plot. Scores for tolerance for iron toxicity were collected from each experimental plot as well as from guard rows. For each experimental plot, the score of susceptible check (averaged over two guard rows) constitutes the value of the covariate for that plot. Data on the tolerance score of each variety (Y variable) and on the score of the corresponding susceptible check (X variable) are shown below:

Scores for tolerance for iron toxicity (Y) of 15 rice varieties and those corresponding guard rows of a susceptible check variety (X) in a RCB trial

Variety Number	Replication I		Replication II		Replication III
Variety Number	X	Y	X	Y	X	Y
1	5	2	6	3	6	4
2	6	4	5	3	5	3
3	5	4	5	4	5	3
4	6	3	5	3	5	3
5	7	7	7	6	6	6
6	6	4	5	3	5	3
7	6	3	5	3	6	3
8	6	6	7	7	6	6
9	7	4	5	3	5	4
10	7	7	7	7	5	6
11	6	5	5	4	5	5
12	6	5	5	3	5	3
13	5	4	5	4	6	5
14	5	5	5	4	5	3
15	5	4	5	5	6	6

MS-EXCEL DATA FILE

Perform analysis of covariance by taking tolerance score of each variety (Y) as dependent variable and score of the corresponding susceptible check (X)
as covariate.
Perform all possible pair wise variety comparisons and identify the best variety.

Analysis Using SAS Analysis Using SPSS