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SAS Certified Associate: Programming Fundamentals Using SAS 9.4 free exam pdf & A00-215 useful dumps are the best choice for you

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SASInstitute A00-215 Exam is an essential certification for individuals who want to pursue a career in data analysis, business intelligence, and programming using SAS. It offers a comprehensive assessment of a candidate's proficiency in SAS programming, data manipulation, and data analysis. Passing A00-215 exam demonstrates the candidate's ability to write, debug, and maintain SAS code, as well as their knowledge of essential SAS procedures and data manipulation techniques.

To prepare for the exam, candidates should have a basic understanding of programming concepts and experience working with data. SAS offers a range of training courses and resources to help candidates prepare for the exam, including e-learning courses, certification prep guides, and practice exams. Candidates can also gain hands-on experience with SAS programming by working on sample projects and data sets.

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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q231-Q236):

NEW QUESTION # 231
You have a SAS dataset called 'SALES' with variables 'Region', 'Product', and 'SalesAmount'. You need to create a report that displays the total sales amount for each region, but only for products with a 'Product' value of 'A' or 'B'. Which of the following PROC SQL statements would achieve this?

Answer: D,E

Explanation:
Both options A and B will achieve the desired result- Option A uses the 'IN operator to check if the 'Product' value is either 'A' or Option B uses the 'OR' operator to achieve the same result Both options correctly group the data by 'Region' and calculate the total sales amount using the SUM function. Option C uses the 'AND' operator, which will only select observations where 'Product' is both 'A' and which is not what is desired. Option D groups the data by both 'Region' and 'Product, which will give a separate total sales amount for each product within each regiom Option E uses a HAVING clause, which is applied after the GROUP BY operation and is used to filter groups based on aggregate functions, not individual observations.

NEW QUESTION # 232
You have a dataset with a variable 'DateOfBirth' in the format 'DDMMYYYY'. You want to display this variable in the format 'MMDDYY' using a format statement. Which SAS code snippet correctly defines and applies the format?

Answer: B

Explanation:
The format 'mmddyy8.' is used to display the date in the 'MMDDYY' format. The format 'mmddyy' is a standard format, but 'mmddyy8.' is a special format for dates in the 'MMDDYY' format with a total of eight characters (i.e., two digits for MM, two digits for DD, and four digits for YY). Option A uses 'mmddyyl 0.1, which would lead to a date format with ten characters (two digits for MM, mto digits for DD, two digits for YY, and four spaces) which is not the desired format. Option C uses 'mmddyy6.', which is not a valid format for dates in the 'MMDDYY' format with eight characters. Option D uses 'mmddyy.', which is not a valid format for dates in the 'MMDDYY' format. Option E uses 'yymmdd10.', which would display the date in the 'YYMMDD' formatr not the desired 'MMDDYY' format.

NEW QUESTION # 233
You have a SAS dataset named 'CUSTOMERS' with the following structure: Customer_lD,First_Name,Last_Name,Email 123,John,Doe,john.doe@example.com 456,Jane,Smith,jane.smith@example.com 789,Peter,Jones,peter.jones@example.com You need to export this data to a CSV file named 'customers_export.csv' with the following requirements: 1. The data should be exported in a specific order: 'Customer ID', 'Last Name', 'First Name', 'Email'. 2. The data should be delimited by a semicolon (;) instead of the default comma (,). 3. The 'Email' column should be enclosed in double quotes ("). Which of the following PROC EXPORT statements would achieve this correctly? (Select all that apply)

Answer: B,C,D

Explanation:
The correct options are A, C, and E. Here's why: PROC EXPORT is used to export SAS datasets to external files. DATA=CUSTOMERS specifies the SAS dataset to be exported. OUTFILE='customers_exportcsv' indicates the location and name of the CSV file to be created- DBMS=CSV specifies the type of data source as a CSV file. REPLACE ensures any existing file with the same name is ovenvritten. PUTNAMES=YES tells SAS to include variable names in the first row of the CSV file- DELIMITER=';' sets the delimiter to a semicolon (;). QUOTECHAR='"' encloses the 'Email' column values within double quotes. ORDER=Customer_lD Last _ Name First_Name Email specifies the desired order for the columns. Option A correctly uses the PROC EXPORT statement to achieve the desired formatting and column order Option C uses a DATA step to enclose the 'Email' column values in double quotes before exporting- The code uses the double quote character (") in conjunction with the concatenation operator (II) to achieve this- This approach allows the data to be formatted in the specified way, as expected for this scenario. Option E uses a DATA step to enclose the 'Email' column values in double quotes before exporting. This approach uses the single quote character (') in conjunction with the concatenation operator (II) and double quotes (") to achieve this. This is also a valid solution and will produce the desired output Why other options are incorrect Option B. Attempts to use the QUOTE() function, which is not a valid function in SAS- The QUOTE() function is available in some other programming languages but not within SAS Option D: Uses unnecessary additional quote characters that will result in incorrect formatting of the 'Email' column. Since the QUOTECHAR option is already specified as "", the extra quotes will lead to incorrect output when exporting to the CSV file.

NEW QUESTION # 234
You have a dataset with a variable 'SALES' containing values like 123.45, 67.89, 90.12. You need to round these values to the nearest integer. Which SAS code snippet accomplishes this correctly?

Answer: A,B

Explanation:
Both options A and E achieve the desired result of rounding to the nearest integer. Option A uses the 'round' function without specifying the number of decimal places, implicitly rounding to the nearest integer. Option E explicitly uses 'round(SALES, 0)' to round to 0 decimal places, achieving the same outcome. Options B, C, and D use different functions (INT, FLOOR, CEIL) that do not provide the intended rounding behavior.

NEW QUESTION # 235
You have a dataset with a variable 'SALES' containing sales values. You need to create a new variable 'SALES CATEGORY' that categorizes sales as follows: - 'High' if SALES is greater than or equal to 10000 - 'Medium' if SALES is greater than or equal to 5000 but less than 10000 - 'Low' if SALES is less than 5000 Which code snippet correctly achieves this using the INT function?

Answer: A

Explanation:
The correct code snippet uses the INT function to divide the sales value by 5000 and then categonzes the results into 'High', 'Medium', and 'Low' based on the integer value obtained. Option D correctly uses the INT function to group the sales values into appropriate categories, using a conditional logic based on the integer value to assign the correct sales category. Other options either use incorrect logic for categorization or do not use INT function effectively for grouping the sales values.

NEW QUESTION # 236
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