A00-215 PDF試験材料2025年最新の実際に出るA00-215問題集 [Q89-Q104]

A00-215 PDF試験材料2025年最新の実際に出るA00-215問題集

更新されたのはSASInstitute A00-215問題集PDFオンラインエンジン

SASInstitute A00-215（SAS Certified Associate：Programming Fundamentals Using SAS 9.4）試験は、SASの基本的なプログラミングコンセプトの理解を検証する認定資格です。この試験は、データ分析、ビジネスインテリジェンス、およびSASを使用したプログラミングに興味がある個人を対象に設計されています。A00-215試験では、SASプログラミング、データ操作、およびデータ分析の候補者の能力を包括的に評価します。

SASInstitute A00-215認定試験は、データ入力や操作、データ分析やレポート作成、SASプログラミングの基礎など、SASプログラミングの概念や技術に関する知識を試験します。この試験は、個人がSASソフトウェアを使用して現実の問題を解決する能力を評価し、より高度なSAS認定資格の基礎を提供することを目的としています。

 

質問 # 89
You have a dataset named 'CUSTOMER' with a variable 'REGION' that categorizes customers into different geographical regions. You need to generate a frequency report showing the count of customers in each region, but you do not want to display cumulative frequencies or percentages. Which PROC FREQ statement achieves.

• A.
• B.
• C.
• D.
• E.

正解：E

解説：
The correct answer is A The ' NOCIJM' and 'NOPERCENT options in the "TABLES statement specifically suppress the display of cumulative frequencies and percentages, respectively. The 'OUTPCT option in option D is used to generate output percentages, which is not the desired outcome. Options B, C, and E do not suppress either cumulative frequencies or percentages.

質問 # 90
You have a dataset called 'SALES' with variables 'REGION', 'PRODUCT', and 'SALES AMOUNT'. You want to calculate the average sales amount for each region, but only for products with a sales amount greater than 1000. Which SAS code snippet would accomplish this?

• A.
• B.
• C.
• D.
• E.

正解：D

解説：
Option C is the correct answer- It uses the PROC MEANS procedure to calculate the mean of 'SALES_AMOUNT' for each region. The WHERE clause ensures that only sales amounts greater than 1000 are included in the calculation. The OUTPUT statement creates a new dataset called 'SALES SUMMARY with the calculated averages. Option A and D are incorrect because they calculate the average within the data step without grouping by region. Option B is incorrect because it does not filter for sales amounts greater than 1000. Option E is incorrect because it uses PROC SQL which is a different approach from the DATA step.

質問 # 91
The sashelp. class data set has 19 observations.
Given the frequency information about the Age, shown below:

How many observations are written to output data set when the following code is submitted?

• A. preteen will have 7 observations and teen will have 19 observations
• B. preteen will have 26 observations and teen will have 31 observations
• C. preteen will have 10 observations and teen will have 9 observations
• D. preteen will have 7 observations and teen will have 12 observations

正解：D

解説：
The code creates two datasets, preteen and teen, based on the age variable from the sashelp.class dataset. The if statement checks each observation, and if the age is less than 13, the observation is written to the preteen dataset; otherwise, the observation is written to the teen dataset.
From the provided frequency table, we can see that there are 7 observations with ages less than 13 (2 for age
11 and 5 for age 12), so the preteen dataset will have 7 observations. Since the sashelp.class dataset has a total of 19 observations, the remaining 12 observations (19 total - 7 preteen = 12 teen) will be written to the teen dataset.
Thus, the answer is: B. preteen will have 7 observations and teen will have 12 observations.
References:
* SAS documentation on the DATA step and IF-THEN/ELSE logic, SAS Institute.

質問 # 92
Which PROC PRINT step correctly displays only the first 10 observations in the data set?

• A. proc print data=sashelp.class(obs=l10);
  run;
• B. proc print data=sashelp.class (oba<'10' )
  ; run;
• C. proc print data=sashelp.class obs=10;
  run;
• D. proc print data=sashelp.class;
  obs=10;
  run;

正解：D

質問 # 93
You have a SAS data set called 'raw_data' with variables 'name', 'city', 'age', and 'occupation'. You want to create a new data set called 'processed_data' that contains only observations where the 'occupation' is 'Doctor' or 'Nurse' and the 'age' is greater than 40. You also want to add a new variable 'status' to the processed data set. The 'status' variable should be assigned 'High Risk' if the 'age' is greater than 60, 'Medium Risk' if the age is between 40 and 60, and 'Low Risk' if the age is less than 40. Which of the following code snippets correctly implements this transformation?

• A.
• B.
• C.
• D.
• E.

正解：E

解説：
The correct answer is E. Here's why: 1. Filtering: The code correctly filters observations where the 'occupation' is either 'Doctor' or 'Nurse' and 'age' is greater than 40. This is achieved using the 'if occupation in ('Doctor', 'Nurse') and age > 40 then do;' statement. 2. Status Variable: The code correctly assigns the 'status' variable based on the 'age' criteria: - If age is greater than 60, 'status' is assigned 'High Risk'. - If age is between 40 and 60, 'status' is assigned 'Medium Risk'. - If age is less than 40, 'status' is assigned 'Low Risk'. This is implemented using the nested IF-THEN-ELSE statements. 3. Logical Operators: The code uses the correct logical operators and conditions to ensure that the 'status' variable is assigned correctly for each observation that passes the initial filtering criteria. Why other options are incorrect: - A: The 'Low Risk' condition is not correctly implemented in the ELSE statement. - B: The code only checks for the 'Medium Risk' condition and does not consider the other risk categories. - C: The 'Medium Risk' condition is not correctly implemented in the ELSE IF statement. - D: While the code includes all three risk categories, the condition for 'Medium Risk' is unnecessarily complex and can lead to potential errors.

質問 # 94
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?

• A.
• B.
• C.
• D.
• E.

正解：A

解説：
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.

質問 # 95
You are generating a report with PROC REPORT and have defined a complex set of break levels. You want to add a footnote at the end of each break level (e.g., at the bottom of each group or subtotal) that provides additional context or explanations for the data within that break. Which of the following approaches will achieve this placement of footnotes effectively?

• A. Employ the FOOTNOTE statement with the SAT PAGE option, and use the 'BREAK statement to control where the footnote should appear within the page.
• B. Utilize the 'DEFINE statement with the T-OOTNOTE option to create a separate column for the footnote, then use the SAT LEVEL' option within the FOOTNOTE statement.
• C. Include the FOOTNOTE statement within the 'BREAK statement for each level, ensuring the footnote is positioned at the end of each break.
• D. Use the FOOTNOTE statement with the 'AT LEVEL' option, specifying the break level where the footnote should appear.
• E. Combine the FOOTNOTE statement with the SAT LEVEL' option and the 'BREAK statement to ensure accurate positioning at each break level.

正解：D

解説：
The correct option is A: Use the FOOTNOTE statement with the 'AT LEVEL' option, specifying the break level where the footnote should appear. This approach allows for precise placement of footnotes at specific break levels within the report. Option B is incorrect because the FOOTNOTE statement cannot be placed within the 'BREAK statement. Options C and D are not supported syntax for the FOOTNOTE statement. Option E is a combination of A and B and is also incorrect.

質問 # 96
You are tasked with importing a CSV file containing financial dat
a. The file has a header row, but some columns have missing values represented by empty strings. You want to import these missing values as SAS missing values (.) rather than empty strings. Which PROC IMPORT option would you use to achieve this?

• A. OUT=dataset
• B. REPLACE-YES
• C. GUESSINGROWS=MAX
• D. MISSING-YES
• E. DBMS=CSV

正解：D

解説：
The option tells PROC IMPORT to treat empty strings as missing values. The other options are not relevant to handling missing values: OUT=dataset specifies the output dataset name, DBMS=CSV indicates the file type, REPLACE=YES ovenvrites existing datasets, GUESSINGROWS=MAX specifies the maximum number of rows to use for guessing data types, and tells PROC IMPORT to use all rows to infer data types.

質問 # 97
You have a dataset with customer purchase records, including their customer ID, purchase date, and purchase amount. You want to calculate the average purchase amount for each customer but only for the purchases made in the last three months. Using the DATA step, how would you modify the code to achieve this, taking advantage of BY group processing with FIRST. and LAST. variables?

• A. count-0; end; if then do; avg_amount+purchase_amount; count+l; end; output; run; data customer_avg; set purchases; by customer_id; retain avg_amount 0 count 0; if first.customer_id then do; avg_amount=0;
• B. data customer_avg; set purchases; by customer_id; retain avg_amount 0 count 0; if first.customer_id then if intck('month' , purchase_date,
• C. data customer_avg; set purchases; by customer_id; retain avg_amount 0; count=0; if first.customer_id then count+l; if then avg_amount+purchase_amount; output; run; data customer_avg; set purchases; by customer_id; retain avg_amount 0 count 0; if first.customer_id then do; avg_amount=0;
• D. =3 then do; avg_amount+purchase_amount; count+l; end; output; run; data customer_avg; set purchases; by customer_id; retain avg_amount 0; if first.customer_id then if intck('month' , purchase_date, today())< =3 then avg_amount+purchase_amount; output; run;
• E. count-0; end; if intck('month',purchase_date,today())<=3 then do; avg_amount=purchase_amount; count+l; end; output; run;

正解：B

解説：
Option D is the correct answer because it correctly initializes the 'avg_amount' variable to zero for each customer's first record, it only considers purchases within the last three months, and it calculates the average by dividing the accumulated purchase amount by the count of transactions within the three-month window. Options A, B, C, and E either incorrectly initialize the variables or do not correctly compute the average within the specific time frame.

質問 # 98
You're working with a dataset that contains employee salary information. You need to adjust the salary based on the following criteria: - If the employee is in the 'Management' department and their salary is less than $50,000, increase their salary by 10%. - If the employee is in the 'Sales' department and their salary is between $40,000 and $60,000, increase their salary by 5%. - Otherwise, leave the salary unchanged. Which of the following code snippets accurately implements this logic using the IF-THEN/ELSE structure?

• A.
• B.
• C.
• D.
• E.

正解：E

解説：
The correct code snippet is option A Here's why: 1. ' 'Department and Salary Conditions: '' Option A correctly uses 'and' to combine the department condition with the salary condition within each 'if statement This ensures that the salary adjustment is applied only when both conditions are met. 2. ''ELSE Statement'' The 'else statement at the end of the code handles the case where neither the management nor sales condition is true, ensuring that the salary remains unchanged for these employees. Options B, C, and D use 'do' blocks unnecessarily The code would be less efficient and potentially more complex with the unnecessary 'do' blocks. Option E is missing the 'else' statement, meaning that salaries for employees outside the specific conditions would not be adjusted. Remember to include the 'else' to ensure that salaries are updated for all employees.

質問 # 99
You are tasked with creating a SAS program to calculate the average income for each state in a dataset. You have a dataset called "income" with variables "State" and "Income". Which of the following SAS code snippets will correctly calculate the average income for each state?

• A.
• B.
• C.
• D.
• E.

正解：A、C、E

解説：
The following code snippets correctly calculate the average income for each state: - Option A: The PROC MEANS procedure calculates summary statistics for numerical variables, and the BY statement groups the results by state- - Option B. The PROC SQL procedure uses a SQL statement with the AVG() function to calculate the average income for each state, grouped by state using GROUP BY - Option D. The PROC SUMMARY procedure calculates summary statistics for variables and the CLASS statement specifies the grouping variable (state) and the VAR statement specifies the variable for which the mean is calculated_ The OUTPUT statement creates a new dataset with the calculated average income. The other options are incorrect - Option C: This code snippet attempts to calculate the average income within the data step, but it does not handle the group by state requirement. - Option E: The PROC FREQ procedure is used to calculate frequencies and cross-tabulations, not summary statistics like average income.

質問 # 100
You are analyzing a dataset containing customer transactions with a 'Transaction_Date' variable in the format 'YYMMDDI You need to create a new variable called 'Days_Since Last_Transaction' that calculates the number of days between each transaction for each customer, sorted by 'CustomerlD' and 'Transaction_Date'. Which code snippet correctly performs this calculation?

• A.
• B.
• C.
• D.
• E.

正解：E

解説：
The correct answer is "A". The 'intck' function is used to calculate the number of intervals between two dates. In this case, we are using the ''days" interval to calculate the number of days between the current transaction date and the previous transaction date for each customer. The 'lag' function is used to access the value of the previous observation for the same variable. Option B is incorrect because it calculates the difference in days between the current transaction date and the previous transaction date, which is the opposite of what we want to achieve. Option C is incorrect because it uses the ''day" interval instead of the ''days" interval. Option D is incorrect because it uses the 'intnx' function, which is used to add or subtract a specified number of intervals from a date. Option E is incorrect because it simply subtracts the previous transaction date from the current transaction date, which does not accurately calculate the number of days between them.

質問 # 101
You are analyzing a dataset of sales transactions with various product categories. You want to sort the data by sales amount in descending order, but only within each product category. Which PROC SORT statement would achieve this?

• A.
• B.
• C.
• D.
• E.

正解：E

解説：
The correct code snippet is option C. It sorts the data first by ProductCategory in ascending order, then within each category, by SalesAmount in descending order This achieves the desired sorting within each category. Option A sorts only by ProductCategory and SalesAmount together, not within each category. Option B sorts only by SalesAmount, disregarding product categories. Option D sorts by ProductCategory in descending order, which may not be the intended behavior. Option E is incorrect because it uses two separate BY statements, which will not achieve the desired sorting within each category.

質問 # 102
You are tasked with analyzing sales data for different regions. You need to calculate the cumulative sum of sales for each region, resetting the sum at the start of each new region. Which of the following code snippets would correctly achieve this, using BY group processing with FIRST. and LAST. to accumulate in groups?

• A.
• B.
• C.
• D.
• E.

正解：A

解説：
Explanation: Option A is correct The code uses the FIRST-region variable to identify the start of a new region. If it's the first observation for the region, cumulative_sales is initialized to 0. The statement 'cumulative_sales + sales;' accumulates the sales for each observation within the region. Options B, C, D, and E contain errors. Option B initializes cumulative_sales only for the first region, not for subsequent regions. Options C, D, and E do not reset cumulative_sales at the beginning of each region, leading to incorrect cumulative sums.

質問 # 103
You have a SAS dataset named 'ORDERS' with the following structure: Order ID,Customer ID,Order Date,T0tal Amount You need to export this data to a CSV file named 'orders_export.csv' with the following requirements: 1. The data should be sorted by 'Order Date' in ascending order. 2. The 'Order Date' column should be formatted as 'YYYY-MM-DD'. 3. The 'Total Amount' column should be formatted as a comma-separated numeric value with 2 decimal places. Which of the following PROC EXPORT statements would achieve this correctly?

• A.
• B.
• C.
• D.
• E.

正解：D

解説：
The correct option is E. Here's why: PROC EXPORT is used to export SAS datasets to external files. DATA-ORDERS specifies the SAS dataset to be exported. OUTFILE='orders_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 overwritten. PUTNAMES=YES tells SAS to include variable names in the first row of the CSV file. FORMAT Order_Date=DATE9. Total_Amount=COMMA12.2 applies the desired formatting to the specified columns. DATE9_ formats the 'Order_Date' column as 'YYYY-MM-DD', while COMMA12.2 formats the 'Total_Amount' column as a comma-separated numeric value with 2 decimal places. SORT BY Order_Date sorts the dataset by the 'Order_Date' column in ascending order before exporting it to the CSV file. Why other options are incorrect: Option A: Uses YYMMDDIO. format, which is not the desired format for the 'Order_Date' columm Option B. Doesn't sort the data before exporting. Option C: Uses DOLLAR 12.2 format, which is not appropriate for the 'Total_Amount' column. Option D: Doesnt sort the data before exporting, and uses the OUT-ORDERS clause, which is not required within the SORT statement inside PROC EXPORT

質問 # 104
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