While conventional statistical methods usually assume that the error  term in the models are independent and identically distributed (i.i.d.), this assumption is usually violated when observations are interdependent due to the strategic interactions among players. The violation of the i.i.d assumption results in the inefficient estimation of standard errors that can further invalidate the hypothesis testing. This paper discusses the method of statistical backward induction (SBI) developed by Curtis S.