This question uses the airquality dataset available with R$.$ This data reports the Ozone$($Ozone level$),$ Solar.R $($Solar radiation$),$ Wind $($Wind speeds$)$ and Temp $($Temperature$)$ for each day for some months in New York city.

Load the airquality dataset from the package datasets into the dataframe aQ by typing the following commands.

library$($datasets$)$

aQ $<-$ airquality

head$($aQ$)$

a$)$ Run a simple regression with Ozone level as the dependent variable and Wind speed as the independent variable. Show only the R$-$code.

b$)$ Use the summary command to display regression output. Show the R$-$code and the results. Write down the regression model using the coefficient values.

c$)$ Based on the summary of the regression, comment on fit $($R$-$squared$)$ and significance of the regression. What conclusion can you draw on the impact of Wind on Ozone level?

d$)$ Using the regression model, predict the average Ozone level for day with wind speeds of$10.$ Show the R$-$code the results.

e$)$ Plot the scatter plot of Ozone level versus Wind speed and the regression line using ggplot $.$ Show the R code and output.