Factorial Design Analysis

In the above stated equation, the yi is the evaluated outcome for the ith unit of value; Bo is the value of the intercept which is the value of beta, B1 is the difference of the two values included in factor 1, similarly the B2 is also the mean value for the related factors of the model that might be factor 2. Beta B3 is the value of interaction of the factor 2 and 3; e is the residual value that is the possibilities of errors in the model. This analysis model involves the dummy variables in the study which are denoted by Z and in the 2×2 factorial models the dummy variables present two main effects and one interaction. The values of the dummy coded variables comprises of 0 and 1 value that is 0 is allotted with control group and 1 is allotted in case of the treatment group. The model most commonly involves the adjustment of the beta values with the variable Z. As the model includes two dummy variables with the involvement of two values, then the equation can be separately written for the maximum number of times as presented in the factorial design. It can also be written as the two equations with Z. In result of these equations, the more appropriate effect is shown.

References

• Das, M.N., and Giri, N.C., (2003), Design and analysis of experiments. Ed. 2nd:New age international publishers.
• Keisler, H.J. and Robbin, J., (1996), Mathematical Logic and Computability.