An effect will be said to be estimable if, and only if, there is a contrast in the data which has for its expectation the particular effect biased only by other effects which we choose to suppress. Experimental designs in which main effects are aliased with each other are of no interest. Hence, it is noted that the resolution of experimental designs is very important in the effect analysis process.
Considering 
full factorial design, this
experiment has 1 degree-of-freedom for the main effects on factors A and B
and 4 degree-of-freedom for the
two-factor interaction AB
.
Hence, this design clearly estimates the main effects and two-factor interaction
effect.
Now, let’s consider the fractional factorial design of 
with 
. The aliasing effects can be easily
determined by multiplying 
and
by effects.
These relations show that the design will estimate the aliased
effects such as 
, 
, 
and 
. From the definition of the Resolution
III, design should be
used when the main effects are nearly independent from two-factor or higher
effects in the system.