Smoothness　of　the　regression　function　is　unknown　in　practical　applications,　so　it　isn＇t　reasonable　to　assume　the　smoothness.　This　paper　investigates　a　regression　model　based　on　size-biased　random　samples,　and　proves　the　mean　consistency　of　two　wavelet　estimators　without　assuming　any　smooth　conditions　of　the　regression　function.　Numerical　experiments　indicate　that　regression　functions　given　by　the　two　wavelet　estimators　are　closer　to　the　true　regression　function　as　the　size　of　sample　increasing.　Especially,　they　are　almost　same　as　the　true　regression　function　when　the　size　of　sample　is　1000.　Numerical　experiments　support　the　main　theorem.　The　results　can　be　considered　as　a　supplement　of　Chesneau　and　Shirazi＇s　work.　©,　2015,　Beijing　University　of　Technology.　All　right　reserved.