ANOVA for response latency

getwd()

## [1] "C:/Users/manne_000/Desktop"

setwd("C:\\Users\\manne_000\\Desktop\\mannerist")

res.anova <- read.csv("res_anova.csv")
head(res.anova)

##     d.type   i.type       ratio
## 1 attitude attitude 0.020100503
## 2 attitude attitude 0.032258065
## 3 attitude attitude 0.025423729
## 4 attitude attitude 0.011461318
## 5 attitude  factual 0.072847682
## 6 attitude  factual 0.009370817

res.a1 <- aov(ratio ~ d.type + i.type, data=res.anova)
summary(res.a1)

##             Df  Sum Sq  Mean Sq F value Pr(>F)
## d.type       1 0.00038 0.000383   0.139  0.713
## i.type       1 0.00370 0.003698   1.340  0.259
## Residuals   23 0.06349 0.002761

res.lm <- lm(ratio ~ d.type + i.type, data=res.anova)

summary(res.lm)

## 
## Call:
## lm(formula = ratio ~ d.type + i.type, data = res.anova)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.06748 -0.02718 -0.01093  0.01829  0.17749 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)   
## (Intercept)    0.052327   0.015351   3.409  0.00241 **
## d.typefactual -0.008502   0.021187  -0.401  0.69190   
## i.typefactual  0.024522   0.021187   1.157  0.25898   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.05254 on 23 degrees of freedom
## Multiple R-squared:  0.06039,    Adjusted R-squared:  -0.02131 
## F-statistic: 0.7392 on 2 and 23 DF,  p-value: 0.4885

errorbar plot for response latency

setwd("C:\\Users\\manne_000\\Desktop\\mannerist")
eb <- read.csv("errorbar.csv")
eb

##                type    avr     sd  n     se
## 1         태도-태도 0.0430 0.0281 10 0.0089
## 2     태도-사실관계 0.0924 0.0907  6 0.0370
## 3     사실관계-태도 0.0594 0.0333  6 0.0136
## 4 사실관계-사실관계 0.0450 0.0354  4 0.0177

library(ggplot2)

ggplot(eb, aes(x=type, y=avr)) + geom_point(size=4) +
  geom_errorbar(aes(ymax = avr + se*1.98, ymin = avr - se*1.98), width=.2) +
  theme(axis.text=element_text(size=15),
        axis.title=element_text(size=16,face="bold"))