Hi, sure. In analyzing experiments, it's assumed that interactions between different factors are statistically insignificant between three-or-more factors.
From the
Individual factors may be significant, i.e., produce a noticeable effect on the ( value of the) dependent variable. Then we consider the interaction effect between pairs, triplets, quadruplets ( 4-ples) of factors on the dependent variable.
We may do a regression ,
Y=a1*x1+a2*x2+...+an*xn+ [ b1*x1x2 + b2*x1x3+...+]+ [c1*x1x2x3+...]+..+[k1*x1x2...xn]
where Y is the dependent variable , x1,x2,.., xn are the independent variables, and ai*xi denotes the effect of the variable xi, etc.and the term bj*xixj denotes/describe the effect of the interaction between the variables xi, xj in our regression, and cj*xixkxm is the term for the interaction of the independent variables xi,xk, xm. Interactions between triplets- or- higher of effects are assumed not to have much effect on the dependent variable.
https://en.m.wikipedia.org/wiki/Sparsity-of-effects_principle