Both options A and D are correct. They use the BY statement and the LAST-CUSTOMER_ID system variable to identify the last record for each customer. Option A uses OUTPUT to write the last record for each customer to the output dataset. Option D accomplishes the same result by implicitly outputting the last record for each customer. Option B is incorrect because it simply merges the datasets without filtering for the most recent order. Option C is incorrect because it uses _N_ = 1, which is only true for the first record of each customer and not the last. Option E is incorrect because it tries to assign ORDER DATE to itself, which is redundant and does not guarantee that the last order date is captured.

Option A is the correct WHERE statement. It directly calculates the total sales value (QUANTITY ' PRICE) for each observation and filters out observations where this value exceeds 1000. Option B is incorrect because SUM is an aggregate function used for calculating sums across a dataset, not within an observation. Option C is incorrect because it assumes the existence of a variable 'TOTAL SALES' which is not defined in the question. Option D is the same as option A making it redundant. Option E is the same as option B, making it redundant. The WHERE clause is applied during the data step's input phase, selectively reading only the observations that meet the specified conditions.

The correct statements are. B. Semicolons are mandatory at the end of every SAS statement This signifies the end of the statement for the SAS compiler ' ''C:'' Comments are enclosed within P and They are ignored by the SAS compiler and are used for documentation purposes- E. SAS supports nested data steps. This allows for more complex and structured logic within data processing. Lets discuss why the incorrect statements are false. A. SAS keywords are NOT case-sensitive. SAS interprets keywords regardless of capitalization. For example, 'DATA' is the same as 'data' - ' SAS variables can include alphanumeric characters, underscores, and the @ sign. This allows for more descriptive and flexible variable names.

Option D is the correct solution. Using the 'LABEL' statement within 'PROC DATASETS' and 'MODIFY' allows you to permanently change the display name of the 'ProductName' variable without altering the actual variable name. Option A is incorrect because it attempts to rename the variable, which would permanently change the variable name itself_ Option B is incorrect because it uses the 'LABEL' statement in a 'DATA' step, resulting in temporary label assignment Option C is incorrect because it applies the label within a 'PROC PRINT' step, which only changes the display name within that specific procedure and does not persist in the dataset. Option E is incorrect because it permanently modifies the value of the 'ProductName' variable by replacing 'Product' with 'Item' within the data itself, rather than just changing the display name. This question tests your understanding of using the 'LABEL' statement to control the display name of variables in reports without altering the variable names or data values. It highlights the distinction between temporary and permanent changes within SAS-

The correct answer is A. The MAXDEC= option within the PROC MEANS statement directly controls the number of decimal places displayed for all calculated statistics. Option B uses a FORMAT statement to format the output variable, but it doesn't affect the underlying calculations. Option C uses the OUTPUT statement to create a new dataset, but it doesn't specify the decimal place display. Option D combines both MAXDEC= and the OUTPUT statement, which would create a dataset but also limit the decimal places displayed. Option E applies the format to the calculated average (avg_roi) within the PROC MEANS procedure, but won't affect the displayed output of the overall statistics. The correct statement is A as it directly applies MAXDEC= to the procedure and thus all output statistics.