1.Refer to yearly sales data (yearly_sales.csv) to answer following questions via R commands

a.Downloadthe"yearly_sales.csv"fromCanvasandimportittoR/RStudio.Saveittosales object.

b.Check whether the imported CSV in the sales object is data frame or not.

c.Display structure of the sales object.

d.Display the summary of this data set with the summary command.

e.Plot number of orders vs. sales.

f.Add a new column to the above data for average sales per order as total sales divided by number of orders to the rightmost via R command and submit the resultant CSV file.

g.Extract this new column (average sales per order) as a new variable and find the average of average sales per order.

h.Create new column categorizing the total sales into three groups/levels: small, medium andlargewithsmallaslessthan100,mediumasgreaterthanorequalto100andlessthan 500andbigasgreaterthanorequalto500.Namethisnewcolumnassales_group.

i.Build a contingency table based on the gender and the newly created sales_group column.

j.Find correlation and covariance between the total sales and number of orders.