$*$ Use the word file Casez$\_$README for detailed question prompts for this case. # R code goes on the line after each question pronpt # Qoa # Use the read.csv$()$ function to read in the data. ###$$N Name your object train and don't forget the strings$=$T argunent. # Q$0$b # Use the Library$()$ function to load the gantr Library. # $01$ # Use the sum$()$ and is$.$na$()$ functions in a single line of code NHANHW to count the total number of NAs in the dataset. # Q$2.$ Use the sum$()$ and is$.$na$()$ functions in a single tine of code ######H# to count the number of hones that $*$do note have a lot frontage recorded. # Q$3$ # Use the sun$()$ and is$.$ na$()$ functions in a single line of code ##AH## to count the number of hoses that $*$do$*$ have a lot frontage recorded. # Q$4$ # Use the mean$()$ function to compute the average ##ANANH Lot frontage of the homes in this dataset. # $05$ # Use the mean$()$ function to conpute the average #AN### lot frontage for a home with at least $1$ fireplace. # $06$ # Use the mean$()$ function to compute the average Annnn# sales price for a home with lot configuration recorded as corner. # $07$ # Use tapply$()$ to compute the mean sales price, ###$$ broken out by lot configuration. ###HANH# tapply$()$ is explained in the README in the Canvas assignment! # Q$8$ # Type a line of code: naref$($train$,$ inpute $=$T $)$ ###NHANH and give it the object nane trImp $($short for "train imputed"$).$ # $09$ # Use the sum$()$ and is$.$na$()$ functions in a ##$$## single line of code on the trimp datafrase to verify #HNNW# there are no missing values in your inputed data frame.