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評判のSASInstitute A00-215認定試験の問題集

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SASInstitute A00-215認定試験は、SAS 9.4を使用したSASプログラミングの基礎知識を証明したい個人にとって高く評価されている認定資格です。この認定試験は、SASプログラミングの基礎知識を持ち、データ操作、データ分析、SASを使用したレポート作成のスキルを向上させたい個人を対象としています。

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A00-215試験の準備方法｜ユニークなA00-215対応資料試験｜実際的なSAS Certified Associate: Programming Fundamentals Using SAS 9.4基礎問題集

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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 認定 A00-215 試験問題 (Q132-Q137):

質問 # 132
Which PROC MEANS program creates the report below?

A. Pror moans data-uashelp . shoes sum mean nobe;
by sales;
class product
B. proc means data-sashelp. shoes sum mean;
var Sales;
Class Product;
run;
C. proc means data-esea= ashelp. shoes.
sum Salad;
mean Sales;
by product;
run."
D. proc means data=sashelp. 'shoes
var Sale;
group Product;
run/

正解：B

解説：
The PROC MEANS statement is used to compute descriptive statistics of data in SAS. Option A is the correct code to produce the report shown in the first image because of the following reasons:
* data=sashelp.shoes specifies the dataset on which the procedure is to be performed.
* sum mean specifies that the summary statistics should include the sum and mean of the variables.
* var Sales; specifies that the variable Sales is the analysis variable for which the summary statistics are to be computed.
* class Product; specifies that the procedure should classify results by unique values of the Product variable. This will produce separate statistics for each type of product, which aligns with the structure of the report provided in the image.
Options B, C, and D are incorrect for the following reasons:
* B uses group instead of class, and group is not a valid statement in the context of PROC MEANS.
Also, var Sale; is incorrect as the variable name is Sales.
* C includes nobe; which is not a valid SAS option and seems to be a typo. The by statement is used for sorting data, not for classifying groups as class does.
* D incorrectly uses sum Salad; and mean Sales; as separate statements and has an invalid use of by product; which is not needed here.
References:
* SAS 9.4 documentation for the PROC MEANS statement: SAS Help Center: PROC MEANS

質問 # 133
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?

正解：A、B、C、D、E

解説：
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' '.

質問 # 134
Which variable in the Program Data Vector represents the number of times the Data step has iterated?

A. _Obs_
B. _N_
C. N
D. Obs

正解：B

解説：
Explanation
https://v8doc.sas.com/sashtml/lrcon/z0961108.htm

質問 # 135
You have a dataset containing employee information, including their 'Department' and 'Salary' variables. You want to create a frequency report for the 'Department' variable, but you want the departments to be displayed in the order of their average salary (highest average salary first). Which of the following options would achieve this?

正解：E

解説：
The correct answer is E. The ORDER-ASCENDING option sorts the rows in ascending order based on the values of the variable, but we need to calculate the average salary for each department first. This can be done by using the PROC MEANS procedure to calculate the average salary for each department. Then, you can use the 'SORT' procedure to sort the departments based on their average salary. Finally, you can use PROC FREQ with the ORDER-ASCENDING option to display the departments in the desired order. The other options are incorrect because they sort based on different criteria, and the information provided does not suggest the need for descending order. While the 'ORDER=FORMATTED' option might appear relevant because it allows you to define a format for the output, it does not automatically sort based on average salaries. The 'ORDER=DATA' option sorts based on the order the values appear in the input dataset, which might not be in the desired order of average salaries. The 'ORDER=FREQ' option sorts the rows based on the frequency of each category, which is not relevant to the goal of sorting by average salary The DESCENDING)' option sorts by internal storage order, which is not helpful in this context

質問 # 136
You have a dataset with customer transactions. You want to calculate the running total of each customer's transactions, but only for transactions within a specific time period. Which of the following approaches would be the most efficient and accurate for achieving this, using BY group processing with FIRST. and LAST. To accumulate in groups?

A. Use a single DATA step with a BY group processing for customer and transaction date. Use FIRST. and LAST variables to identify the beginning and end of the time period for each customer, and calculate the running total within that period.
B. Use a separate DATA step for each customer, calculate the running total within the time period, and merge the results.
C. Use a PROC SQL query with a window function to calculate the running total for each customer within the specified time period.
D. Use a combination of PROC SQL and the DATA step. Use PROC SQL to filter the transactions within the time period and then usethe DATA step to calculate the running total for each customer.
E. Use a macro to create a separate DATA step for each customer, calculate the running total, and then merge the results.

正解：A

解説：
Option B is the most efficient and accurate approach- It leverages BY group processing with FIRST. And LAST to identify the specific time period for each customer. It avoids the overhead of creating separate DATA steps or PROC SQL queries, making it more efficient. Option A would be inefficient due to multiple DATA steps and merging. Option C, while possible, might not be as efficient as the DATA step solution. Option D introduces unnecessary complexity with macros. Option E is also a viable approach, but it may not be as efficient as using a single DATA step with BY group processing.

質問 # 137
......

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A00-215基礎問題集: https://www.jptestking.com/A00-215-exam.html

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