time <- read.csv("C:/Users/Shalini/Downloads/delivery_time.csv")
View(time)
plot(time)

colnames(time)

## [1] "Delivery.Time" "Sorting.Time"

cor(time)

##               Delivery.Time Sorting.Time
## Delivery.Time     1.0000000    0.8259973
## Sorting.Time      0.8259973    1.0000000

delivery <- lm(log(time$Delivery.Time)~log(time$Sorting.Time))
summary(delivery)

## 
## Call:
## lm(formula = log(time$Delivery.Time) ~ log(time$Sorting.Time))
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.23303 -0.09050 -0.00825  0.08897  0.36439 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             1.74199    0.13312  13.086 5.92e-11 ***
## log(time$Sorting.Time)  0.59752    0.07446   8.024 1.60e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1558 on 19 degrees of freedom
## Multiple R-squared:  0.7722, Adjusted R-squared:  0.7602 
## F-statistic: 64.39 on 1 and 19 DF,  p-value: 1.602e-07