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Analysis of Data from Designed Experiments

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 Example: {Nigam, A.K. and Gupta V.K., 1979, Handbook on Analysis of Agricultural experiments, First Edition, I.A.S.R.I. Publication, New Delhi, pp16-20}.A feeding trial with 3 feeds namely (i) Pasture(control), (ii) Pasture and Concentrates and (iii) Pasture,  Concentrates and Minerals was conducted at the Yellachihalli Sheep Farm, Mysore, to study their effect on wool yield of Sheep. For this purpose twenty-five ewe lambs were allotted at random to each of the three treatments and the three treatments and the weight records of the total wool yield (in gms) of first two clipping were obtained. The data for two lambs for feed 1, three for feed 2 and one for feed 3 are missing. The details of the experiment are given below:

Yield (in gms)

FEED 1

FEED 2

FEED 3

850.50

510.30

992.25

453.60

963.90

850.50

878.85

652.05

1474.20

623.70

1020.60

510.30

510.30

878.85

850.50

765.45

567.00

793.80

680.40

680.40

453.60

595.35

538.65

935.55

538.65

567.00

1190.70

850.50

510.30

481.95

850.50

425.25

623.70

793.80

567.00

878.85

1020.60

623.70

1077.30

708.75

538.65

850.50

652.05

737.10

680.40

623.70

453.60

737.10

396.90

481.95

737.10

822.15

368.55

708.75

680.40

567.00

708.75

652.05

595.35

652.05

538.65

567.00

567.00

850.50

595.35

453.60

680.40

.

652.05

.

.

567.00

.

.

.

MS-EXCEL DATA FILE

Where  Feed 1- Pasture (control),

Feed 2- Pasture and Concentrates and

Feed 3- Pasture, Concentrates and Minerals.

 

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

2. Perform all possible pair wise treatment comparisons and identify the best treatment i.e. the treatment giving highest yield.                                                                                                                                                                                                    

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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,
 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)