Parameter　sensitivity　analyses　have　been　widely　applied　to　industrial　problems　for　evaluating　parameter　significance,　effects　on　responses,　uncertainty　influence,　and　so　forth.　In　the　interest　of　simple　implementation　and　computational　efficiency,　this　study　has　developed　two　sensitivity　analysis　methods　corresponding　to　the　situations　with　or　without　sufficient　probability　information.　The　probabilistic　method　is　established　with　the　aid　of　the　stochastic　response　surface　and　the　mathematical　derivation　proves　that　the　coefficients　of　first-order　items　embody　the　parameter　main　effects　on　the　response.　Simultaneously,　a　nonprobabilistic　interval　analysis　based　method　is　brought　forward　for　the　circumstance　when　the　parameter　probability　distributions　are　unknown.　The　two　methods　have　been　verified　against　a　numerical　beam　example　with　their　accuracy　compared　to　that　of　a　traditional　variance-based　method.　The　analysis　results　have　demonstrated　the　reliability　and　accuracy　of　the　developed　methods.　And　their　suitability　for　different　situations　has　also　been　discussed.　©　2014　Sheng-En　Fang　et　al.