all questions

\#Q1 \# Use the nnow() function to find \#\#\#\#\#\# how many homes are available in this dataset. \# Q2 \# Use the ncol() function to find \#\#\#\#\#\# how many variables were recorded for each home. \# Q3 \# Use the mean() function to find the average sales price \#\#\#\#\#\#\# for homes in this data. Hint: Use names(train) \#nNHWW to get the exact spelling of the columns in this dataset. * Q4 \# Later, you will model sales price by features 8 \#nthtH\# and if you model the sales price by month sold, 9 \#\#\#m\#\#\# month should be a factor (a categorical variable). 0 \#\#ABrnthil Use the is.factor() function on the month sold column \# Q5 \# Use the sum() function on a logical vector \#nN to count how many homes have a sales price of $181,600. A Q6 \# There are 4 rating categories for kitchen quality: N fair, average, good, and excellent. Annnnan how many homes have kitchen quality rated as "Excellent"? \#ANNN\# Hint: use the summary() function on the kitchen quality column \# Q7 \# Use the sum() function on a logical vector to count \#nnynnt: how many homes sold for more than $350,000 \# Q8 \# Use the mean() function to find the average sales price \#Hindini for a home with kitchen quality rating of "Excellent". \# Q9 \# Use the mean() function to f ind the average sales price \#\#nank for a home with kitchen quality rating of "Excellent" \#ananan or has a garage for more than 2 cars. * Q1e " Use the which() function on a logical vector to find Hanen the observations number(s) for a home with a whenthil kitchen quality rating of "Excellent" 49 \#anthn and sales price of at most $195,080. 59 \#Q1 \# Use the nnow() function to find \#\#\#\#\#\# how many homes are available in this dataset. \# Q2 \# Use the ncol() function to find \#\#\#\#\#\# how many variables were recorded for each home. \# Q3 \# Use the mean() function to find the average sales price \#\#\#\#\#\#\# for homes in this data. Hint: Use names(train) \#nNHWW to get the exact spelling of the columns in this dataset. * Q4 \# Later, you will model sales price by features 8 \#nthtH\# and if you model the sales price by month sold, 9 \#\#\#m\#\#\# month should be a factor (a categorical variable). 0 \#\#ABrnthil Use the is.factor() function on the month sold column \# Q5 \# Use the sum() function on a logical vector \#nN to count how many homes have a sales price of $181,600. A Q6 \# There are 4 rating categories for kitchen quality: N fair, average, good, and excellent. Annnnan how many homes have kitchen quality rated as "Excellent"? \#ANNN\# Hint: use the summary() function on the kitchen quality column \# Q7 \# Use the sum() function on a logical vector to count \#nnynnt: how many homes sold for more than $350,000 \# Q8 \# Use the mean() function to find the average sales price \#Hindini for a home with kitchen quality rating of "Excellent". \# Q9 \# Use the mean() function to f ind the average sales price \#\#nank for a home with kitchen quality rating of "Excellent" \#ananan or has a garage for more than 2 cars. * Q1e " Use the which() function on a logical vector to find Hanen the observations number(s) for a home with a whenthil kitchen quality rating of "Excellent" 49 \#anthn and sales price of at most $195,080. 59