ighed ▁separately . ▁However , ▁note ▁that ▁the ▁estimates ▁for ▁the ▁items ▁obtained ▁in ▁the ▁second ▁experiment ▁have ▁errors ▁that ▁correlate ▁with ▁each ▁other . ▁ ▁Many ▁problems ▁of ▁the ▁design ▁of ▁experiments ▁involve ▁combin atorial ▁designs , ▁as ▁in ▁this ▁example ▁and ▁others . ▁ ▁A vo iding ▁false ▁posit ives ▁ ▁False ▁positive ▁conclus ions , ▁often ▁resulting ▁from ▁the ▁pressure ▁to ▁publish ▁or ▁the ▁author ' s ▁own ▁confirm ation ▁bias , ▁are ▁an ▁inher ent ▁ha z ard ▁in ▁many ▁fields . ▁A ▁good ▁way ▁to ▁prevent ▁bi ases ▁potentially ▁leading ▁to ▁false ▁posit ives ▁in ▁the ▁data ▁collection ▁phase ▁is ▁to ▁use ▁a ▁double - bl ind ▁design . ▁When ▁a ▁double - bl ind ▁design ▁is ▁used , ▁participants ▁are ▁randomly ▁assigned ▁to ▁experimental ▁groups ▁but ▁the ▁research er ▁is ▁una ware ▁of ▁what ▁participants ▁belong ▁to ▁which ▁group . ▁Therefore , ▁the ▁research er ▁can ▁not ▁affect ▁the ▁participants ' ▁response ▁to ▁the ▁inter vention . ▁▁ ▁Ex perimental ▁designs ▁with ▁und is closed ▁degrees ▁of ▁freedom ▁are ▁a ▁problem . ▁This ▁can ▁lead ▁to ▁conscious ▁or ▁un cons cious ▁" p - h ack ing ": ▁trying ▁multiple ▁things ▁until ▁you ▁get ▁the ▁desired ▁result . ▁ ▁It ▁typically ▁involves ▁the ▁manip ulation ▁- ▁perhaps ▁un cons ci ously ▁- ▁of ▁the ▁process ▁of ▁statistical ▁analysis ▁and ▁the ▁degrees ▁of ▁freedom ▁until ▁they ▁return ▁a ▁figure ▁below ▁the ▁p < . 0 5 ▁level ▁of ▁statistical ▁significance . ▁So ▁the ▁design ▁of ▁the ▁experiment ▁should