1. Use the Excel datafile "Lab2_Vehicles.xlsx" which contains the monthly vehicle sales in the U.S. in 2018. This dataset is constructed from the raw datasets downloaded from Bureau of Economic Analysis. 6). Create a permanent library named lab2. Import "Lab2_Vehicles.xlsx into SAS and store it in "lab2" library. (ii). Based on the imported dataset, create a new SAS dataset: Create a new variable Unit which has the character value 'In Thousands'. Use SAS function to calculate the average, total, maximum, and minimum of the monthly sales from January to December. Name these four variables "Ave_sales", "Total_sales, "Max_sales and Min_sales respectively. Compute the difference between "Max_sales and Min_sales". Name the difference variable Range" Someone predicts that the total sales for each type in 2019 will increase at least by 2%, and at most by 10%. Compute the minimum and maximum predicted total sales in 2019. Compute the predicted minimum and maximum increase of total sales in Year 2019 compared to Year 2018 (iii). Print the newly created dataset. 1. Use the Excel datafile "Lab2_Vehicles.xlsx" which contains the monthly vehicle sales in the U.S. in 2018. This dataset is constructed from the raw datasets downloaded from Bureau of Economic Analysis. 6). Create a permanent library named lab2. Import "Lab2_Vehicles.xlsx into SAS and store it in "lab2" library. (ii). Based on the imported dataset, create a new SAS dataset: Create a new variable Unit which has the character value 'In Thousands'. Use SAS function to calculate the average, total, maximum, and minimum of the monthly sales from January to December. Name these four variables "Ave_sales", "Total_sales, "Max_sales and Min_sales respectively. Compute the difference between "Max_sales and Min_sales". Name the difference variable Range" Someone predicts that the total sales for each type in 2019 will increase at least by 2%, and at most by 10%. Compute the minimum and maximum predicted total sales in 2019. Compute the predicted minimum and maximum increase of total sales in Year 2019 compared to Year 2018 (iii). Print the newly created dataset