. e . ▁there ▁is ▁real ▁cov ari ation ▁between ▁the ▁cause ▁and ▁effect ). ▁Low ▁power ▁occurs ▁when ▁the ▁sample ▁size ▁of ▁the ▁study ▁is ▁too ▁small ▁given ▁other ▁factors ▁( small ▁effect ▁sizes , ▁large ▁group ▁vari ability , ▁un re li able ▁measures , ▁etc .). ▁ ▁Vi ol ated ▁assumptions ▁of ▁the ▁test ▁statistics ▁ ▁Most ▁statistical ▁tests ▁( part icular ly ▁infer ential ▁statistics ) ▁involve ▁assumptions ▁about ▁the ▁data ▁that ▁make ▁the ▁analysis ▁suitable ▁for ▁testing ▁a ▁hypothesis . ▁Vi ol ating ▁the ▁assumptions ▁of ▁statistical ▁tests ▁can ▁lead ▁to ▁incorrect ▁infer ences ▁about ▁the ▁cause - effect ▁relationship . ▁The ▁robust ness ▁of ▁a ▁test ▁indicates ▁how ▁sensitive ▁it ▁is ▁to ▁viol ations . ▁Vi ol ations ▁of ▁assumptions ▁may ▁make ▁tests ▁more ▁or ▁less ▁likely ▁to ▁make ▁type ▁I ▁or ▁II ▁errors . ▁ ▁D red ging ▁and ▁the ▁error ▁rate ▁problem ▁Each ▁hypothesis ▁test ▁involves ▁a ▁set ▁risk ▁of ▁a ▁type ▁I ▁error ▁( the ▁alpha ▁rate ). ▁If ▁a ▁research er ▁searches ▁or ▁" d red ges " ▁through ▁their ▁data , ▁testing ▁many ▁different ▁hypoth eses ▁to ▁find ▁a ▁significant ▁effect , ▁they ▁are ▁infl ating ▁their ▁type ▁I ▁error ▁rate . ▁The ▁more ▁the ▁research er ▁repeatedly ▁tests ▁the ▁data , ▁the ▁higher ▁the ▁chance ▁of ▁obser ving ▁a ▁type ▁I ▁error ▁and ▁making ▁an ▁incorrect ▁inference ▁ ▁about ▁the ▁existence ▁of ▁a ▁relationship . ▁ ▁Un re li ability ▁of ▁measures ▁If ▁the ▁dependent ▁and / or ▁independent ▁variable (