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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q114-Q119):

NEW QUESTION # 114
You have a dataset named 'SALES' with 'PRODUCT ID', 'SALES DATE', and 'QUANTITY SOLD' variables. You need to create a new dataset that summarizes the total quantity of each product sold in the last two weeks. How would you use the IN= option and a temporary dataset to achieve this?

Answer: E

Explanation:
This solution uses the 'IN=S option to filter the 'SALES' dataset to include only records from the last two weeks (using 'INTNX('WEEK' Then, it uses a second data step to create a summary dataset ('SUMMARY), grouping by 'PRODUCT _ ID' and calculating the sum of 'QUANTITY_SOLD for each product ''Explanation of other options. B. The date range is incorrect- It only includes the second-to-last week, not the last two weeks- ' This option directly creates the 'SUMMARY' dataset without first filtering the data, leading to an incorrect sum. ' ''D:'' This option includes data from the current week as well, which is incorrect based on the requirement for the last two weeks- ' ''E'' This option only considers the last week, not the last two weeks.

NEW QUESTION # 115
You are tasked with generating a report with PROC REPORT that includes a footnote explaining the source of the dat a. How can you add the footnote using the FOOTNOTE statement?

Answer: B

Explanation:
The correct syntax for adding a footnote in PROC REPORT is using the FOOTNOTE statement followed by the footnote text enclosed in single quotes. The other options use incorrect syntax or apply options not relevant to footnotes.

NEW QUESTION # 116
You have a dataset 'EMPLOYEES' with 'ID', 'NAME', 'SALARY', and 'DEPARTMENT' variables. You need to create a new dataset 'HIGH SALARY DEPT' containing only employees who have a salary higher than the average salary of their respective department. Which combination of statements would achieve this?

A. PROC SQLI CREATE TABLE HIGH SALARY DEPT AS SELECT ' FROM EMPLOYEES WHERE SALARY > (SELECT AVG(SALARY) FROM EMPLOYEES GROUP BY DEPARTMENT); QUIT;
B. DATA HIGH SALARY DEPT, SET EMPLOYEES, WHERE SALARY > (SELECT AVG(SALARY) FROM EMPLOYEES GROUP BY DEPARTMENT); RUN
C. DATA HIGH SALARY DEPT, SET EMPLOYEES, IF SALARY > (SELECT AVG(SALARY) FROM EMPLOYEES GROUP BY DEPARTMENT) THEN OUTPUT, RUN,
D. DATA HIGH SALARY DEPT, SET EMPLOYEES, WHERE SALARY > AVG(SALARY) BY DEPARTMENT RUN,
E. DATA HIGH SALARY DEPT, SET EMPLOYEES, WHERE SALARY > AVG(SALARY) BY DEPARTMENT RUN,

Answer: A,B

Explanation:
Both options B and D are correct and will achieve the desired result. Option B uses PROC SQL to achieve the same outcome. It creates a new table 'HIGH SALARY DEPT' by selecting all employees from 'EMPLOYEES' where their salary is greater than the average salary for their respective department This is accomplished using a subquery within the WHERE clause. Option D uses the DATA step with a subquery within the WHERE clause to select only the employees who meet the condition- The subquery uses a SELECT statement with AVG(SALARY) grouped by the DEPARTMENT to compute the average salary for each department It is then compared to the employee's salary to determine if it's higher. Option A is incorrect because the WHERE statement cannot use the aggregate function AVG in this way within the DATA step. Option C is also incorrect because it tries to use the SELECT statement within an IF statement which is not allowed in SAS- Option E is the same as Option A and incorrect for the same reason- The WHERE clause is applied during the data step's input phase, selectively reading only the observations that meet the specified conditions.

NEW QUESTION # 117
You have a dataset containing product information, including a variable named 'Category' with values such as 'Electronics', 'Clothing', 'Food', and 'Furniture'. You want to create a report that displays the total sales for each category, but you want to group 'Food' and 'Furniture' together under a new label 'Home & Living'. Which approach would you use?

A. PROC SOL; SELECT SUM(Sales), CASE WHEN Category IN ('Food', 'Furniture') THEN 'Home & Living' ELSE Category END AS Category FROM Your Data set GROUP BY Category; RUN;
B. PROC PRINT DATA=Your Data set; LABEL Category = 'Home & Living' WHEN (Category='Food' OR Category-'Furniture'); RUN;
C. PROC SUMMARY DATA-Your Data set; CLASS Category; VAR sales; OUTPUT OUT-Summary; LABEL Category = 'Home & Living' WHEN OR Category='Furniture'); RUN;
D. PROC MEANS DATA=Your Data set; CLASS Category; VAR sales; LABEL Category = 'Home & Living' WHEN (Category='Food' OR Category='Furniture'); RUN;
E. PROC REPORT DATA-Your Data set; CLASS Category; DEFINE Sales / SUM; LABEL Category = 'Home & Living' WHEN (Category='Food' OR Category-'Furniture'); RUN;

Answer: A

Explanation:
The correct answer is B. PROC SQL allows you to create a new variable that groups the desired categories using a CASE statement and the IN operator. The code 'SELECT SUM(Sales), CASE WHEN Category IN ('Food', 'Furniture') THEN 'Home & Living' ELSE Category END AS Category FROM YourDataset GROUP BY Category' groups the 'Food' and 'Furniture' categories under 'Home & Living' while maintaining the original 'Electronics' and 'Clothing' categories, calculating the total sales for each group. Option A is incorrect as the LABEL statement in PROC SUMMARY doesn't support the WHEN clause_ Option C is incorrect because PROC REPORT doesn't have the LABEL statement, and while it has WHEN clause, its used for defining attributes for report columns. Option D is incorrect as PROC PRINT is not suitable for grouping categories and calculating sums. Option E is incorrect as the LABEL statement in PROC MEANS only allows for assigning labels to existing values, not creating new groups.

NEW QUESTION # 118
You have two SAS datasets: 'CUSTOMERS' (CUSTOMER ID, NAME) and 'ORDERS' (ORDER D, CUSTOMER ID, ORDER DATE). You want to create a new dataset 'CUSTOMER ORDERS' that includes customer information and their most recent order date. Which code snippets would achieve this correctly? (Select all that apply)

Answer: C,D

Explanation:
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.

NEW QUESTION # 119
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