Mainly there are four experimental design models.
- Completely Randomized Design (CRD)
- Random Completely Block Design (RCBD)
- Split Plot Design
- Latin Square Design (LSD)
Completely Randomized Design (CRD)
Experimental unit in the population has an equal equally treated with the treatments/randomly treated.
E.g. – Effect of the fertilizer is monitored of crop cultivation, plants (Experimental unit) are randomly treated fertilized A (treatment).
Random Completely Block Design (RCBD)
Population is divided into block (each block contains similar experimental unit) blocks are homogenate, then treatments are applied randomly to each blocks.
E.g. – Effect of the fertilizer A,B,C,D on banana crops, in the population there is a 100 plants, make 5 blocks each containing 20 plants fertilizer A,B,C,D is applied randomly for each block. block are made base on the soil type each block have similar soil properties in order to avoid the soil properties influence the crop yield.
Split Plot Design
A variation of RCBD design. Experimental units is divided into large block and within large block there are small blocks (subplots). main treatment is applied to large block and the secondary treatment is applied to subplots.
E.g. – Effect of individual and the mixture of the fertilizer (A,B,A+B), large blocks are treated with fertilizer A, subplot are treated with the fertilizer B (small plots are treated with fertilizer A and B (A+B))
Both split plot design and RCBD blocks have similar character (soil type, topology….), similar amount of experimental unit(number of plants should be similar).
Latin Square Design (LSD)
Equal number of rows, column and treatments are used.
E.g. – Effect of fertilizer (rows) A,B,C on different soil types (Columns) (clay, slit, sand),each treatment (row) occurs once in each row and column.
| clay (Col 1) | slit (Col 2) | sand (Col 3) | |
| fertilizer A | A | C | B |
| fertilizer B | B | A | C |
| fertilizer C | C | B | A |
Factorial design
Factorial designs include the multiple variables and examine the effect the two or more independent variables to the response variables(dependent variable)
This design is used to examine the main effect of independent variables and interaction of the factors (independent variables)
E.g. – Examine the temperature and the light intensity on the crop yield, for this 2*2 factorial design is used. the four conditions are
- high temperature, high light intensity
- high temperature,low light intensity
- low temperature,high light intensity
- low temperature/low light intensity