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Analysis of Data from Designed Experiments

Split Plot Design 



Analysis Using SAS 

Analysis Using SPSS


 Main Procedure is:  


Start →All Programs → SPSS for Windows → SPSS 15.0/ SPSS13.0/ SPSS10.0 (based on the version available on your machine) → Enter data in Data Editor → Analyze → GLM → Univariate  → yield → [puts yield under Dependent list: ] rep → [put rep under Fixed Factor(s): ]   ms → [put ms under Fixed Factor(s):]  mt → [put mt under Fixed Factor(s):]  Continue → Model... [Opens Model dialogue box] Custom → Build Term(s) → Main effects  →[puts rep, ms, mt under Model: ] Interactionrep var spt  [puts rep*ms and ms*mt  under Model:] → Run All.



Data Input:

For performing analysis, input the data in the following format. {Here one can call the replication as rep, main-plot treatments as ms (method of sowing) and sub-plot treatments as mt (manorial treatment). (It may, however, be noted that one can retain the same name or can code in any other fashion).


 Following are the brief description of the steps along with screen shots.

         Open Data editor: Start All Programs SPSS for Windows SPSS 15.0/ SPSS13.0/  SPSS10.0  



         Enter data in SPSS Data Editor. There are two views in SPSS Data Editor. In variable view, one can define the name of variables and variable types string or numeric and data view gives the spreadsheet in which data pertaining to variables may be entered in respective columns. In the present case, entered data is in numeric format.




         Once the data entry is complete, Choose Analyze from the Menu Bar. Now select Analyze → General linear Model → Univariate.  





  • This selection displays the following screen:  




  • Select yield and send it to the Dependent Variable rep, ms and mt may be selected for Fixed Factor(s) box. This selection displays the following screen:


  • For the Interactions select Model in the Univariate dialog box i.e. Model... [Opens Model dialogue box] Interaction rep ms [puts rep*ms under Model:].Similarly ms*mt can also be put under the model.


This selection displays the following screen.




         Click  Continue to return to the Univariate dialog box .



Syntax for testing mainplot with error(a).


Click Paste on the Univariate dialog box to get the commands in syntax editor. Now define model as per design adopted to analyze the data. Here it is  /Test ms vs rep*ms.




         Click Run → All.





To perform the analysis, the following syntax may be used after creating the data file.










We could not find the syntax for pairwise comparisons by selecting the appropriate error term. For making all possible pairwise comparisons, one may, however, compute only the means from the software and compute the minimum significant differences using the given formulae on the click of mouse.


Data File

Syntax File

Result File


   Analysis Using SAS                                                      Analysis Using SPSS                                       



Home 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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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
(Under Development)

For exposure on SAS, SPSS, 
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 (