Assignment 3

Question 1

data('mtcars')

cor.test(mtcars$mpg , mtcars$wt)

## 
##  Pearson's product-moment correlation
## 
## data:  mtcars$mpg and mtcars$wt
## t = -9.559, df = 30, p-value = 1.294e-10
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.9338264 -0.7440872
## sample estimates:
##        cor 
## -0.8676594

# The more a car weighs, the less MPG it gets

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

# Load necessary package
library(ggplot2)

# Create scatter plot
ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point() +
  labs(title = "The more a car weighs, the less MPG it gets",
       x = "Weight (1000 lbs)",
       y = "Miles Per Gallon") +
  theme_minimal()

# Load the plotly package
library(plotly)

# Create the scatter plot with a trendline
plot_ly(mtcars, x = ~wt, y = ~mpg, type = 'scatter', mode = 'markers', name = 'Data') %>%
  add_trace(x = ~wt, y = fitted(lm(mpg ~ wt, data = mtcars)), 
            mode = 'lines', name = 'Trendline', line = list(color = 'blue'))