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Analysis of Data from Designed Experiments

Resolvable Block Design

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Example:  An initial varietal trial was conducted to study the performance of 21 new strains of Toria vis-a-vis 3 checks using an alpha design at Pantnagar with three replications. The seed yield in kg/ha was recorded. The details of strains, design adopted and data obtained are given as under.

Treatment  Treatment No. Treatment  Treatment No. Treatment  Treatment No.
RAU DT-01-03 1 TK-06-1 9 RH-0304 17
RAU DT-01-02 2 TK-06-2 10 TH-0302 18
BAUSM-92-24 3 TL-2027 11 JMT-05 19
RGN 186 4 TL-2013 12 PT-303(NC) 20
EJ-17 5 JMT-02-6 13 Zonal Check 21
NPJ-112 6 NDT 05-5 14 PTC-99-14 22
VLT-4 7 NDRE 200216 15 JD-6(check) 23
RRN-612 8 PT-2004-3 16 ORT 17-6-16 24

Note: strains of toria in boldface are the three checks, i.e., treatment numbers 20, 21 and 23 are checks.

Replication 1

Block 1 1 (1555.6) 5 (1160.5) 9 (1308.6) 13 (1382.7) 17 (987.7) 21 (1135.8)
Block 2 2 (1284.0) 6 (1086.4) 10 (1284.0) 14 (1111.1) 18 (938.3) 22 (1308.6)
Block 3 3 (1234.6) 7 (419.8) 11 (1308.6) 15 (963.0) 19 (963.0) 23 (987.7)
Block 4 4 (1234.6) 8 (987.7) 12 (1284.0) 16 (913.6) 20 (1160.5) 24 (790.1)

Replication 2

Block 1 1 (1481.5) 6 (1086.4) 11 (1308.6) 16 (1284.0) 19 (1111.1) 22 (1185.2)
Block 2 2 (987.7) 7 (308.6) 12 (1234.6) 13 (1308.6) 20 (765.4) 23 (938.3)
Block 3 3 (1012.3) 8 (864.2) 9 (1234.6) 14 (938.3) 17 (913.6) 24 (864.2)
Block 4 4 (1135.8) 5 (987.7) 10 (987.7) 15 (740.7) 18 (963.0) 21 (1135.8)

Replication 3

Block 1 1 (1284.0) 7 (333.3) 12 (1135.8) 15 (839.5) 18 (814.8) 24 (888.9)
Block 2 2 (1135.8) 8 (913.6) 9 (1456.8) 16 (1037) 19 (938.3) 21 (1037.0)
Block 3 3 (963.0) 5 (1209.9) 10 (1259.3) 13 (1234.6) 20 (963.0) 22 (1111.1)
Block 4 4 (1086.4) 6 (765.4) 11 (1111.1) 14 (1037.0) 17 (938.3) 23 (938.3)

MS-EXCEL DATA FILE

Figures in the parenthesis gives the seed yield in kg/ha.

1. Perform the analysis of variance of the data to test whether there is any difference between treatment effects.

2. Obtain the adjusted treatment means.

3. Test whether there is any significant different treatment from the best performing test.

Analysis Using SAS                                                        Analysis Using SPSS                                    

 

 

 

 

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Descriptive Statistics
Tests of Significance
Correlation and Regression
Completely Randomised Design
RCB Design
Incomplete Block Design
Resolvable Block Design
Augmented 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
Cluster Analysis
Groups of Experiments
Non-Linear Models
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Other Designed Experiments
    
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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 Resources Server (www.iasri.res.in/design)