Stimulus 1
###normality check
sti1_Acc <- read.table("sti1_Acc.txt", header=TRUE)
shapiro.test(sti1_Acc$valid)
##
## Shapiro-Wilk normality test
##
## data: sti1_Acc$valid
## W = 0.91534, p-value = 0.4725
shapiro.test(sti1_Acc$invalid)
##
## Shapiro-Wilk normality test
##
## data: sti1_Acc$invalid
## W = 0.96784, p-value = 0.8776
shapiro.test(sti1_Acc$invalid_hori)
##
## Shapiro-Wilk normality test
##
## data: sti1_Acc$invalid_hori
## W = 0.96766, p-value = 0.8764
shapiro.test(sti1_Acc$invalid_verti)
##
## Shapiro-Wilk normality test
##
## data: sti1_Acc$invalid_verti
## W = 0.8663, p-value = 0.2119
###paired ttest
t.test(sti1_Acc$valid,sti1_Acc$invalid,paired=T)
##
## Paired t-test
##
## data: sti1_Acc$valid and sti1_Acc$invalid
## t = 0.89298, df = 5, p-value = 0.4128
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.07631985 0.15756985
## sample estimates:
## mean of the differences
## 0.040625
t.test(sti1_Acc$invalid_hori,sti1_Acc$invalid_verti,paired=T)
##
## Paired t-test
##
## data: sti1_Acc$invalid_hori and sti1_Acc$invalid_verti
## t = -0.56298, df = 5, p-value = 0.5978
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.08117118 0.05200451
## sample estimates:
## mean of the differences
## -0.01458333
###effect size
Exp1_eff<- cohen.d(sti1_Acc$valid,sti1_Acc$invalid,paired=T)
print.effsize(Exp1_eff)
##
## Cohen's d
##
## d estimate: 0.3645592 (small)
## 95 percent confidence interval:
## inf sup
## -0.9324989 1.6616173
Exp1_eff_2<- cohen.d(sti1_Acc$invalid_hori,sti1_Acc$invalid_verti,paired=T)
print.effsize(Exp1_eff_2)
##
## Cohen's d
##
## d estimate: -0.2298358 (small)
## 95 percent confidence interval:
## inf sup
## -1.520493 1.060821
Stimulus 2
normality check
###normality check
sti2_Acc <- read.table("sti2_Acc.txt", header=TRUE)
shapiro.test(sti2_Acc$valid)
##
## Shapiro-Wilk normality test
##
## data: sti2_Acc$valid
## W = 0.84478, p-value = 0.1427
shapiro.test(sti2_Acc$invalid)
##
## Shapiro-Wilk normality test
##
## data: sti2_Acc$invalid
## W = 0.92337, p-value = 0.53
shapiro.test(sti2_Acc$invalid_hori)
##
## Shapiro-Wilk normality test
##
## data: sti2_Acc$invalid_hori
## W = 0.90186, p-value = 0.385
shapiro.test(sti2_Acc$invalid_verti)
##
## Shapiro-Wilk normality test
##
## data: sti2_Acc$invalid_verti
## W = 0.94299, p-value = 0.6834
###paired ttest
t.test(sti2_Acc$valid,sti2_Acc$invalid,paired=T)
##
## Paired t-test
##
## data: sti2_Acc$valid and sti2_Acc$invalid
## t = 3.4281, df = 5, p-value = 0.01867
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.01537406 0.10754261
## sample estimates:
## mean of the differences
## 0.06145833
t.test(sti2_Acc$invalid_hori,sti2_Acc$invalid_verti,paired=T)
##
## Paired t-test
##
## data: sti2_Acc$invalid_hori and sti2_Acc$invalid_verti
## t = -2.5904, df = 5, p-value = 0.04881
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.0788642248 -0.0003024419
## sample estimates:
## mean of the differences
## -0.03958333
###effect size
Exp2_eff<- cohen.d(sti2_Acc$valid,sti2_Acc$invalid,paired=T)
print.effsize(Exp2_eff)
##
## Cohen's d
##
## d estimate: 1.399535 (large)
## 95 percent confidence interval:
## inf sup
## -0.035749 2.834820
Exp2_eff_2<- cohen.d(sti2_Acc$invalid_verti,sti2_Acc$invalid_hori,paired=T)
print.effsize(Exp2_eff_2)
##
## Cohen's d
##
## d estimate: 1.057516 (large)
## 95 percent confidence interval:
## inf sup
## -0.3158763 2.4309077