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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q270-Q275):

NEW QUESTION # 270
Consider the following SAS code:

During the compilation and execution of this code, which of the following statements are TRUE about the process of assigning values to the variable 'AGE GROUP'? Choose all that apply.

A. The order of the IF conditions is crucial, as only the first TRUE condition will determine the value of 'AGE GROUP'.
B. The assignment of 'AGE GROUP' occurs during the execution phase, after the DATA step has read a record from the input dataset.
C. The 'AGE GROUP' variable will be assigned a value only when the corresponding IF condition is evaluated to TRUE.
D. The compiler will generate a warning if any record has an 'AGE' value not matching any of the IF conditions.
E. The 'AGE GROUP' variable will be assigned a default value of 'Child' if none of the IF conditions evaluate to TRU

Answer: A,B,C

Explanation:
The 'AGE_GROUP' variable is assigned a value based on the first IF condition that evaluates to TRUE, and only that condition- If none are TRUE, it remains unassigned. B) is correct. The data step reads records from the input dataset (in this case, WORKOLD_DATA), then applies the logic within the code to assign values. This happens during execution, not compilation. C) is correct. The order of the IF conditions matters, as the first one to be evaluated to TRUE will determine the assigned value. If the conditions were reversed, a person aged 25 would be assigned 'Child', not 'Young Adult'. D) is incorrect. The SAS DATA step will not generate a warning for missing conditions. It will simply proceed with assigning the 'AGE GROUP' variable based on the existing logic. E) is incorrect. If none of the IF conditions are TRUE, the 'AGE GROUP' variable will remain unassigned. There is no default value set up for the 'AGE GROUP' variable. If this is not desired behaviour for your data set, the code should be amended to provide a value.

NEW QUESTION # 271
You have a dataset containing a variable 'Full Name' with values like 'John Doe', 'Jane Smith', 'Peter Jones'. You want to extract the last name from each observation and store it in a new variable called 'Last Name'. Which code snippet correctly achieves this using the FIND and SUBSTR functions?

Answer: D

Explanation:
Here's the breakdown: 1. ' locates the position of the first space character in the 'Full_Name' variable, indicating the start of the last name. 2. ,SUBSTR(Full_Name, LENGTH(Full_Name) - FIND(Full_Name, ' + 1 extracts a substring from 'Full _ Name' starting at the position of the space plus 1 (the beginning of the last name) and ending at the length of the string minus the position of the space plus 1 (effectively extracting the last name). Option A extracts the entire string starting from the space plus 1 , which is incorrect_ Option B includes the space in the extracted substring. Option C and E use incorrect calculations for the length of the extracted substring. Only option D accurately extracts the last name.

NEW QUESTION # 272
You have a SAS dataset named 'customer info' that contains detailed customer information. You need to export this data to an Excel file with specific formatting, including column widths, data types, and header labels. Which of the following code snippets correctly utilizes the LIBNAME statement and XLSX engine to achieve this objective?

Answer: A,B,C,D,E

Explanation:
All of the options are valid and achieve different aspects of formatting during the export process- Option A creates the basic export, exporting to a spreadsheet named 'Sheetl' Option B adds the 'COLUMNWlDTff option to specify the desired column widths for the exported data- Option C adds the 'HEADERLABELS' option to provide custom header labels for the exported columns. Option D adds the 'DATATYPE option to define the data types for the exported columns. Option E combines all the previous options to achieve a comprehensive formatting scheme for the exported Excel file. While all options are correct, the most complete and effective solution for formatting is ''Option E' '.

NEW QUESTION # 273
Given the input data set WORK.RUN:

Given the following DATA step:

What is the correct output data set WORK.RUN2?

Answer: B

Explanation:
In the given DATA step, the do weeks=1 to 3; loop iterates three times for each row in the original WORK.RUN dataset, incrementing the miles value by 5 for each iteration and outputting a row after each increment. However, no output; statement is given within the loop to create the extra rows, which means only the last iteration of the loop will be outputted for each original row. Hence, the miles value for each name will be incremented by 15 (5 miles for each of the 3 weeks).
The original data set WORK.RUN has:
John 16
Mary 20
After the DATA step, it should be:
John 31
Mary 35
Each name appears only once because without an explicit output; statement inside the loop, only the final iteration is outputted. The variable weeks is not retained in the output dataset, as it is not used outside the loop and no output statement is used inside the loop. Thus, option D is correct.
References:
* SAS documentation on DATA step processing, SAS Institute.

NEW QUESTION # 274
You have a SAS dataset named 'CUSTOMERS' with variables 'CUSTOMER ID', 'NAME', and 'CITY'. You need to create a new dataset named 'ACTIVE CUSTOMERS' that contains only customers from the city 'New York' and have a purchase date within the last 30 days. Which of the following DATA step code snippets will achieve this correctly?

Answer: E

Explanation:
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.

NEW QUESTION # 275
......

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