Regression

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

summary(d)

##   independent      dependent    
##  Min.   : 1.00   Min.   :17.61  
##  1st Qu.: 5.75   1st Qu.:32.45  
##  Median :10.50   Median :41.41  
##  Mean   :10.50   Mean   :42.33  
##  3rd Qu.:15.25   3rd Qu.:52.91  
##  Max.   :20.00   Max.   :64.16

boxplot(d$independent)

boxplot(d$dependent)

plot(d)

mod<-lm(dependent~independent, data=d)
summary(mod)

## 
## Call:
## lm(formula = dependent ~ independent, data = d)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -17.365  -3.618   1.312   3.383  10.815 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  19.7474     3.0211   6.537 3.83e-06 ***
## independent   2.1511     0.2522   8.530 9.72e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6.503 on 18 degrees of freedom
## Multiple R-squared:  0.8017, Adjusted R-squared:  0.7906 
## F-statistic: 72.75 on 1 and 18 DF,  p-value: 9.723e-08

g1<-ggplot(d,aes(x=independent,y=dependent)) + geom_point() + geom_smooth(method="lm")
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)