paired t test

d<- read.csv("paired.csv")

summary(d)

##        id            before          after      
##  Min.   : 1.00   Min.   :10.10   Min.   :10.37  
##  1st Qu.: 3.25   1st Qu.:12.65   1st Qu.:11.19  
##  Median : 5.50   Median :13.35   Median :14.14  
##  Mean   : 5.50   Mean   :13.02   Mean   :13.56  
##  3rd Qu.: 7.75   3rd Qu.:13.85   3rd Qu.:14.78  
##  Max.   :10.00   Max.   :14.10   Max.   :18.98

t.test(d$before,d$after,paired=TRUE)

## 
##  Paired t-test
## 
## data:  d$before and d$after
## t = -0.68339, df = 9, p-value = 0.5116
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.331587  1.249699
## sample estimates:
## mean of the differences 
##              -0.5409441

d<- read.csv("paired_long.csv")

g1<-ggplot(d,aes(x=time,y=value)) +stat_summary(fun.y=mean,geom="bar",fill="lightgrey",col="black",width=0.7) +stat_summary(fun.data=mean_cl_normal,geom="errorbar",width=0.3)
g1

ylab="My text for the ylabel. Give name of variable and units"
xlab="My text for the xlabel. Give name of variable and units"

g1 + ylab(ylab) + xlab(xlab)

g1<-ggplot(d,aes(x=time,y=value)) + stat_summary(fun.y=mean,geom="point")  +stat_summary(fun.data=mean_cl_normal,geom="errorbar")

g1

ylab="My text for the ylabel. Give name of variable and units"
xlab="My text for the xlabel. Give name of variable and units"

g1 + ylab(ylab) + xlab(xlab)