|Design Resources Server||
Example: An experiment was conducted at Ludhiana Centre of AICRP on Cropping Systems on Maize crop in 1998 kharif season using a balanced confounded design for factorial experiments with three factors viz., Nitrogen (N)(40, 80 and 120 kg/ha), Phosphorus(P) (0, 40 and 80 kg/ha) and Potassium(K)(0 and 40 kg/ha). These 18 treatment combinations were arranged in 3 blocks of size 6 each with 4 replications. To each of the blocks one control treatment was also added. Therefore, there were 7 plots per block and 21 experimental units in each replication. The yield (in kg/plot) is:
levels of different factors have been coded as
(For performing the analysis using original levels,
change coded levels to original level throughout the steps
discussed in sequel).
analysis of variance of the data to test the significance of
the main effects of nitrogen, phosphorus and potassium and
their 2-factor and 3-factor interactions.
significance of 19 treatment combinations and identify the
best treatment combination.
Compare all the
18 treatment combinations with the control treatment.
|Tests of Significance|
|Correlation and Regression|
|Completely Randomised Design|
|Incomplete Block Design|
|Resolvable Block Design|
|Latin Square Design|
|Factorial RCB Design|
|Partially Confounded Design|
|Factorial Experiment with Extra Treatments|
|Split Plot Design|
|Strip Plot Design|
|Response Surface Design|
|Cross Over Design|
|Analysis of Covariance|
|Diagnostics and Remedial Measures|
|Principal Component Analysis|
|Groups of Experiments|
exposure on SAS, SPSS,
available at Design Resources Server (www.iasri.res.in/design)