DESCRIPTIVES VARIABLES=SWS REM /STATISTICS=MEAN STDDEV MIN MAX. CROSSTABS /TABLES=Sleep BY PostKnow BY PreKnow /FORMAT=AVALUE TABLES /CELLS=COUNT /COUNT ROUND CELL. T-TEST GROUPS=Sleep(1 2) /MISSING=ANALYSIS /VARIABLES=SWS REM /CRITERIA=CI(.9500). CORRELATIONS /VARIABLES=SWS REM /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE. CROSSTABS /TABLES=PreKnow BY Sleep /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT EXPECTED ROW COLUMN TOTAL /COUNT ROUND CELL. SORT CASES BY PreKnow. SPLIT FILE SEPARATE BY PreKnow. CROSSTABS /TABLES=Sleep BY PostKnow /FORMAT=AVALUE TABLES /STATISTICS=CHISQ /CELLS=COUNT EXPECTED ROW COLUMN TOTAL /COUNT ROUND CELL. SPLIT FILE OFF. UNIANOVA SWS BY PostKnow PreKnow /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=PostKnow(TUKEY) /PLOT=PROFILE(PostKnow*PreKnow) /PRINT=DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=PostKnow PreKnow PostKnow*PreKnow. * Chart Builder. GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=PreKnow MEANSE(SWS, 1)[name="MEAN_SWS" LOW="MEAN_SWS_LOW" HIGH="MEAN_SWS_HIGH"] PostKnow MISSING=LISTWISE REPORTMISSING=NO /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: PreKnow=col(source(s), name("PreKnow"), unit.category()) DATA: MEAN_SWS=col(source(s), name("MEAN_SWS")) DATA: PostKnow=col(source(s), name("PostKnow"), unit.category()) DATA: LOW=col(source(s), name("MEAN_SWS_LOW")) DATA: HIGH=col(source(s), name("MEAN_SWS_HIGH")) COORD: rect(dim(1,2), cluster(3,0)) GUIDE: axis(dim(3), label("Pre Sleep Knowledge of Mirror Sequence")) GUIDE: axis(dim(2), label("Mean of SWS Percentage During Sleep")) GUIDE: legend(aesthetic(aesthetic.color.interior), label("Post Sleep Knowledge of Mirror ", "Sequence")) SCALE: cat(dim(3), include("1", "2")) SCALE: linear(dim(2), include(0)) SCALE: cat(aesthetic(aesthetic.color.interior), include("1", "2", "3")) SCALE: cat(dim(1), include("1", "2", "3")) ELEMENT: interval(position(PostKnow*MEAN_SWS*PreKnow), color.interior(PostKnow), shape.interior(shape.square)) ELEMENT: interval(position(region.spread.range(PostKnow*(LOW+HIGH)*PreKnow)), shape.interior(shape.ibeam)) END GPL. UNIANOVA REM BY PostKnow PreKnow /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=PostKnow(TUKEY) /PLOT=PROFILE(PostKnow*PreKnow) /PRINT=DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=PostKnow PreKnow PostKnow*PreKnow. * Chart Builder. GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=PreKnow MEANSE(REM, 1)[name="MEAN_REM" LOW="MEAN_REM_LOW" HIGH="MEAN_REM_HIGH"] PostKnow MISSING=LISTWISE REPORTMISSING=NO /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: PreKnow=col(source(s), name("PreKnow"), unit.category()) DATA: MEAN_REM=col(source(s), name("MEAN_REM")) DATA: PostKnow=col(source(s), name("PostKnow"), unit.category()) DATA: LOW=col(source(s), name("MEAN_REM_LOW")) DATA: HIGH=col(source(s), name("MEAN_REM_HIGH")) COORD: rect(dim(1,2), cluster(3,0)) GUIDE: axis(dim(3), label("Pre Sleep Knowledge of Mirror Sequence")) GUIDE: axis(dim(2), label("Mean of REM Percentage During Sleep")) GUIDE: legend(aesthetic(aesthetic.color.interior), label("Post Sleep Knowledge of Mirror ", "Sequence")) SCALE: cat(dim(3), include("1", "2")) SCALE: linear(dim(2), include(0)) SCALE: cat(aesthetic(aesthetic.color.interior), include("1", "2", "3")) SCALE: cat(dim(1), include("1", "2", "3")) ELEMENT: interval(position(PostKnow*MEAN_REM*PreKnow), color.interior(PostKnow), shape.interior(shape.square)) ELEMENT: interval(position(region.spread.range(PostKnow*(LOW+HIGH)*PreKnow)), shape.interior(shape.ibeam)) END GPL.