In this question, we will use flights dataset from $$nycflights$13$ package. Using flight

dataset, $(60$ points$)$

a$)$ write a script to find all flights that Had a departure delay of $12$ or more hours and arrival

delay of $18$ or more hours. $(10$ points$)$

b$)$ write a script to find all Summer flights with Departure in July, August, or September

that are operated by JetBlue Airways $("$B$6")$ that flew from JFK and arrived at MIA or

BQN $(10$ points$)$

c$)$ write a script, using select$()$ function, to select subset of data that include all columns but

the following: distance, hour, minute, time$\_$hour $(10$ points$)$

d$)$ write a script, using mutate$()$ function, to add a new column representing flight operation

costs. In here, the cost of operation for each flight is considered as the sum of air$-$time

cost $($$$5$ per hour of air time$)$ and fly distance cost $($$$3$ per mile traveled$)(10$ points$)$

e$)$ write a script that calculates the correlation between every numerical column in flights

dataset. $(20$ points$)$

Hint: you need to

i$)$ remove all non$-$numerical columns from the dataset using select$()$ function,

ii$)$ you need to remove all missing values $($NA$)$ from your dataset. This can be achieved

by either removing all columns from remaining set that contains missing values $($NA$),$

or removing all rows from dataset that contains missing values $($NA$)$

iii$)$ use cor$()$ function with the trimmed dataset to calculate all pairwise correlations.