The resulting WORK.REVENUE data set contains 3 variables. In the provided SAS program, the set statement uses a (keep=) option to keep only 3 variables from WORK.PRODUCTS, which are ProdId, Price, and Sales. The drop= data set option in the data statement specifies to drop the Sales and Returns variables from the output data set. However, Returns was not included in the keep= option, so it won't be part of WORK.REVENUE to begin with. Finally, a new variable Revenue is calculated and included in the data set. Therefore, the final data set contains the variables ProdId, Price, and Revenue.
References:
* SAS documentation on keep= and drop= data set options.

It uses the 'if statement with a combined logical condition, checking both the 'SALES_AMOUNT' and 'REGION' variables. Only observations where 'SALES_AMOUNT' is greater than 10000 AND 'REGION' is 'North' will be included in the new dataset 'HIGH_SALES'. The 'output' statement explicitly directs the qualifying observations to the new dataset. Options A, C, D, and E either lack the necessary combined condition or have incorrect logical operators, resulting in data subsets that do not match the desired criteria.

Option D uses the INTNX() function to calculate the date a year ago from today, effectively filtering transactions from the past year It then uses the HAVING clause to filter groups based on the count of distinct transactions, ensuring that only customers with at least 3 transactions are included in the average. Option A attempts to use COUNT() within the WHERE clause, which is not valid syntax. Option B uses a correlated subquery within the WHERE clause, but it would not correctly filter transactions from the past year. Option C uses the DATEADD() function, which is not a valid function in SAS. Option E lacks the HAVING clause, meaning it would calculate the average for all customers regardless of the number of transactions.

Both options and are correct. They both filter for orders placed in 2022 using 'if year(Order_Date) = 2022 , then the desired variables ('Product', 'Quantity', 'Price') and calculate 'Total_Value' using 'Total _ Value = Quantity , Price' - They then use an -output' statement within the 'do' loop to create the new dataset 'ORDER _ SUMMARY'. Option A is incorrect because it calculates 'Total_Value' for all observations, regardless of the year, and the 'keep' statement is not within a 'do' loop, so 'Total_Value' might not be included in the output. Option C is incorrect because it tries to 'keep' a non-existing variable 'Total _ Value' before it's calculated. Option E is incorrect because it tries to 'keep' the variables after the 'Total_Value' is calculated, which won't include it in the final output The order of operations matters in this scenario.

The correct answer is A. This LIBNAME statement correctly uses double backslashes to escape the path and points to the directory containing the data set. Options B, C, D, and E are incorrect because they either use incorrect syntax for path specification or do not correctly escape special characters.