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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q230-Q235):

NEW QUESTION # 230
You are analyzing data on customer purchases, and you need to generate a report showing the frequency distribution of purchase amounts categorized by customer age group (18-25, 26-35, 36-45, 46-55, 56+). You also want to examine the relationship between purchase amount and customer gender (Male, Female). Which of the following PROC FREQ statements would correctly accomplish this task and generate the desired output?

Answer: D

Explanation:
Option E is the correct answer. It generates separate frequency distributions for Purchase_Amount by Gender and Age by itself. The FORMAT statement defines a custom AGEGROUP format for the age variable to group ages into the desired categories. Option A attempts to create a three-way table, which may not be the most effective for the analysis. Option B creates two separate tables, one for age and another for purchase amount and gender, which does not effectively address the goal. Option C creates two separate tables, one for purchase amount and another for age and gender. Option D also creates two separate tables, one for purchase amount and gender, and another for age, which does not address the goal. The key to the solution is creating separate tables for the desired analysis while using the correct formatting for the age variable to achieve the desired categorization.

NEW QUESTION # 231
You have a dataset 'EMPLOYEES' with variables 'EMPLOYEE ID', 'DEPARTMENT', and 'SALARY'. You want to create a new dataset 'HIGHEST SALARY BY DEPT' that contains the highest salary for each department. However, you also need to create a variable called 'RANK' that indicates the rank of each employee's salary within their department, with the highest salary being ranked 1. Which of the following DATA step code snippets will achieve this correctly?

Answer: C

Explanation:
Option E is the only correct code snippet that correctly creates the 'HIGHEST_SALARY_BY_DEPT dataset with the highest salary for each department and assigns a rank to each employee within their department. It uses the statement with 'DEPARTMENT to group the data and the 'last. DEPARTMENT ' flag to identify the last observation within each department. The function assigns a rank to each employee's salary within their department, with the highest salary being ranked 1. Option A only outputs the last observation for each department, which is not necessarily the highest salary. Option B only outputs the first observation for each department, which is not necessarily the highest salary. Option C assigns a rank of 1 to all the last observations for each department, which is incorrect Option D assigns a rank of 1 to all the first observations for each department, which is incorrect.

NEW QUESTION # 232
You have a dataset with a variable 'STATUS' containing values 'Active', 'Inactive', 'Pending'. You want to create a custom format 'statusfmt' to display these values as 'A', 'P' respectively, but also handle any unknown values as 'U'. Which PROC FORMAT code achieves this?

Answer: A,D

Explanation:
The correct code snippets are options A and C. They both correctly use the 'OTHER keyword (or its equivalent 'UNKNOWN') in the VALUE statement to handle unknown values. This ensures that any value in the 'STATUS variable that doesn't have a specific mapping in the format will be displayed as 'U'. Option B uses 'DEFAULT which is not a valid keyword for handling unknown values in PROC FORMAT. Options D and E are incorrect because they either reverse the mapping or miss handling unknown values.

NEW QUESTION # 233
You have a dataset called 'Sales' with variables 'Region', 'Product', and 'SalesAmount'. You need to create a new variable called 'Bonus' that assigns a 10% bonus to sales in the 'North' region only if the 'SalesAmount' is greater than $1000. Which code snippet correctly accomplishes this?

Answer: C

Explanation:
Option B is the correct solution. It uses the 'AND' operator to combine the conditions for applying the bonus: the region must be 'North' and the sales amount must be greater than $1000. The 'ELSE' statement assigns a bonus of 0 to all other cases. Options A, C, D, and E are incorrect because they either miss the condition for the sales amount, or they include unnecessary additional conditions, or they dont handle the cases where the bonus shouldn't be applied.

NEW QUESTION # 234
You have a dataset 'Sales' with variables 'Region', 'Product', 'SalesAmount', and 'Quantity'. You need to generate a report that summarizes the average 'SalesAmount' by 'Region' and 'Product' while also calculating the total quantity sold for each product across all regions. How would you modify the PROC MEANS statement to achieve this? Assume you want to generate a separate line in the output for each unique combination of 'Region' and 'Product'.

Answer: D

Explanation:
The correct answer is option E The PROC MEANS statement needs to include both 'Region' and 'Product' in the CLASS statement to generate a separate line for each combinatiom Using 'VAR SalesAmount' calculates the mean of 'SalesAmount'. The OUTPUT statement with 'SUMQTY=SUM(Quantity) I ALL' calculates the total 'Quantity' across all regions for each product Option A incorrectly calculates the sum of 'Quantity' for each combination of 'Region' and 'Product, while option B only calculates the mean and sum by 'Region'- Option C calculates the total 'Quantity' for each 'Region' and 'Product' combination, not across all regions. Option D calculates the mean and sum for 'SalesAmount' and 'Quantity' by 'Product, ignoring 'Region'.

NEW QUESTION # 235
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