Quiz 2025 Useful SASInstitute A00-215: Exam SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Cram Review

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SASInstitute A00-215 exam is a crucial step towards demonstrating proficiency in SAS programming and attaining the SAS Certified Associate credential. With its focus on fundamental programming skills, the exam is suitable for those with limited SAS experience and can help individuals gain recognition for their skills and expertise in SAS programming.

SASInstitute A00-215 (SAS Certified Associate: Programming Fundamentals Using SAS 9.4) is a certification exam that measures an individual's proficiency in SAS programming. A00-215 Exam is designed for individuals who are interested in pursuing a career in data analysis, research, or business intelligence. It is also suitable for professionals who want to validate their SAS programming skills.

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Pass Guaranteed SASInstitute - A00-215 - High Pass-Rate Exam SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Cram Review

The SASInstitute A00-215 Certification is a valuable credential in the modern world. The SASInstitute A00-215 certification exam offers a great opportunity for beginners and experienced professionals to validate their skills and knowledge level. With the one certification SAS Certified Associate: Programming Fundamentals Using SAS 9.4 exam you can upgrade your expertise and knowledge.

To achieve the SASInstitute A00-215 Certification, candidates must pass a 2-hour exam that consists of 65 multiple-choice questions. A00-215 exam covers a wide range of topics, including SAS programming concepts, data manipulation techniques, and basic data analysis. Candidates must have a good understanding of SAS programming concepts, such as data types, variables, functions, and arrays, as well as basic data manipulation techniques, such as merging, sorting, and filtering data.

SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q144-Q149):

NEW QUESTION # 144
You have a dataset named 'SALES' with columns 'REGION', 'PRODUCT', and 'AMOUNT'. You want to create a new dataset named 'HIGH SALES' containing only the records where 'AMOUNT is greater than 1000, and only the 'REGION' and 'PRODUCT' columns should be included. Which SAS code snippet would correctly achieve this?

Answer: E

Explanation:
The correct answer is option D. It uses the 'output' statement to write only those records that meet the condition 'AMOUNT > 1000' to the new dataset 'HIGH_SALES'- The 'keep=REGlON PRODUCT' clause ensures that only the specified columns are included in the output dataset. Option A uses a semicolon instead of 'then' after the 'if statement, which is incorrect syntax- Options B and C incorrectly use a semicolon after 'if statement and do not include the 'keep' option- Option E includes 'drop' option, which will remove the 'AMOUNT' column from the output dataset, while the question asks for 'REGION' and 'PRODUCT' to be included.

NEW QUESTION # 145
Consider the following SAS code:

Which of the following statements are TRUE regarding the SAS data sets created by this code? 1. The data set 'work.new_data' is a permanent SAS data set. 2. The data set 'work.new_data_copy' is a temporary SAS data set. 3. Both data sets have the same structure and dat a. 4. The data set 'work.new data_copy' will be created only if 'work.new_data' already exists. 5. The data set 'work.new_data' will exist only in the current SAS session.

A. 1 and 3
B. 2, 3 and 5
C. 1 and 5
D. 1, 3 and 4
E. 2 and 3

Answer: B

Explanation:
The data set 'work.new_data' is a temporary SAS data set because it is created in the 'work' library. Temporary SAS data sets exist only in the current SAS session. The data set 'work.new_data_copy' is also a temporary SAS data set. Both data sets have the same structure and data because the 'select statement copies all the columns and rows from the original data set. Statement 4 is incorrect because 'create table' statement will always create a new data set. The 'create table' statement does not depend on the existence of the source data set

NEW QUESTION # 146
You have a dataset with a variable 'DATE STR' storing dates in the format 'YYYY-MM-DD'. You want to create a new variable 'DATE NUM' storing the date in numeric format (YYYYMMDD). Which code snippet correctly achieves this transformation?

Answer: D

Explanation:
The correct option is A- The INPUT function is used to convert a character string into a numeric date value. The format 'YYMMDD8.' specifies the input format as 'YYYY-MM-DD' and the output format as numeric date. Option B is incorrect as it uses the 'DATE9_' format which is for a different date format. Options C and E use incorrect input formats. Option D simply assigns the character string to the numeric variable, which is incorrect.

NEW QUESTION # 147
You have a SAS dataset 'TRANSACTIONS' with variables 'TRANSACTION D', 'CUSTOMER ID', 'PRODUCT ID', and 'AMOUNT'. You need to create a dataset 'CUSTOMER TRANSACTIONS containing the total amount spent by each customer. Additionally, you need to include a variable 'NUM TRANSACTIONS' that indicates the number of transactions made by each customer. Which code snippet would you use to achieve?

Answer: B

Explanation:
It uses the 'by' statement to group observations by 'CUSTOMER ID' , initializes 'total amount' and 'num transactionS to 0 for the first observation of each customer, and accumulates the total amount and counts the number of transactions using 'total_amount + AMOUNT and 'num_transactions + 1'. The 'output' statement writes the summarized data to the new dataset 'CUSTOMER _ TRANSACTIONS'. Option B uses and , which calculate the sum and count for the entire dataset instead of grouping by customer. Options C and D omit initialization of 'total_amount' and 'num_transactlons' and use 'total_amount + AMOUNT and 'num_transactions + 1 ' incorrectly without clear accumulation logic. Option E only calculates the total amount spent by each customer, not the number of transactions.

NEW QUESTION # 148
Which program generates the PROC MEANS report below?

A. proc means data=sashelp.class nodec;
class Age; run;
B. proc means data=sashelp. class;
by Age;
run;
C. proc means data=sashelp. class maxdec=0;
var Age;
run;
D. proc means data=sashelp. class;
group Age;
run;

Answer: D

NEW QUESTION # 149
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