Statement 4 - 'John 30;' would result in an error because it is a data line within the CARDS statement and needs to be terminated with a semicolon. In SAS, data lines within the CARDS statement should end with a semicolon (;) to indicate the end of a data line. Without a semicolon, the SAS system interprets the line as incomplete, leading to an error. The other statements are syntactically correct and would execute without errors.

The correct answer is The 'last. PRODUCT statement ensures the calculation is performed only for the last observation of each product group. This allows for the correct summation of 'SALES_AMOUNT for the entire product group before applying the filter. The 'sum(of SALES_AMOUNT)' statement then calculates the sum for each group, and the 'mean(SALES AMOUNT)' calculates the average, outputting the result only if the total sales amount exceeds 1000. Option A uses 'sum(of SALES_AMOUNT)' incorrectly, and option B does not consider the total sales amount for each product before calculating the average. Options D and E use incorrect conditions to filter data.

The correct answer is Option A. It accurately defines the custom format 'REGION FORMAT by explicitly mapping each specified region value to a more descriptive label and using 'OTHER' to handle any other value, including missing values. Options B and C use 'MISSING' or '.' directly, which are not the correct way to handle any non-specified values, including missing values. Options D and E are incorrect because they unnecessarily use both 'OTHER' and or 'MISSING', which can cause unexpected behavior.

It uses the 'by' statement to group observations by 'PRODUCT_ID', initializes 'sum_quantity' to 0 for the first observation of each product, and accumulates the total quantity sold using 'sum_quantity + QUANTITY SOLD. The 'output' statement writes the summarized data to the new dataset 'SALES_SUMMARY. Option B incorrectly uses for the summation. Options C and E use , which calculates the sum for the entire dataset instead of grouping by product. Option D omits initialization of 'sum_quantity' and uses 'sum_quantity + QUANTITY_SOLD incorrectly without a clear accumulation logic.

The correct code snippet is Option C. It uses the ' intnx()' function to calculate the date 30 days ago from the current date ('date()')- The 'if statement then checks if the ' CITY' is 'New York' and the 'PURCHASE DATE is greater than or equal to the date 30 days ago, selecting only active customers from New York. Option A uses the incorrect logic for calculating 30 days ago- Option B uses the 'intnx()' function but incorrectly compares the calculated date to the current date. Option D uses the incorrect operator to filter customers within the last 30 days. Option E uses 'intnx()' with a positive value, calculating the date 30 days in the future, which is not desired.