SASInstitute A00-215 Reliable Exam Pattern | Reliable A00-215 Exam Book
SASInstitute A00-215 Reliable Exam Pattern | Reliable A00-215 Exam Book
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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q241-Q246):
NEW QUESTION # 241
You have an Excel file named 'sales_data.xlsx' with multiple sheets. You want to import data from the sheet named 'QI _ Sales' into a SAS dataset. Which LIBNAME statement should you use to achieve this?
- A.
- B.
- C.
- D.
- E.
Answer: C
Explanation:
Option C is the correct answer. It first defines a LIBNAME named 'excel' that points to the Excel file using the XLSX engine and sets the ACCESS to READONLY. Them it creates a SAS dataset named 'Ql_Sales' and uses the SET statement to read data from the sheet 'QI _Sales' within the 'excel' LIBNAME. Option A is incorrect as it doesn't specify the sheet name. Option B is incorrect because the sheet name should be specified within the SET statement, not in the LIBNAME statement. Option D is incorrect because it doesn't specify the access mode. Option E is incorrect because the OUT= option is not used in the LIBNAME statement for importing data.
NEW QUESTION # 242
Which PROC SORT option allows you to create an output data set of the sorted data?
- A. Data=
- B. OUT=
- C. SORTOUT=
- D. OUTPUT=
Answer: B
Explanation:
In SAS, the PROC SORT procedure is used to sort data. To save the sorted data into a new dataset, the OUT= option is used in the PROC SORT statement. This option allows you to specify the name of the output dataset that will contain the sorted data.
Here is how it's used:
* proc sort data=original out=sorted; by variable; run; will sort the dataset original by variable and create a new dataset named sorted containing the sorted data.
Option A, Data=, is not valid for the PROC SORT procedure. Option B, SORTOUT=, is a common misconception but is not correct; OUT= is the right option. Option C, OUTPUT=, is not used within PROC SORT; it is used in other procedures such as PROC TABULATE and PROC SUMMARY for output datasets.
References:
* SAS 9.4 documentation for the PROC SORT statement: SAS Help Center: PROC SORT
NEW QUESTION # 243
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. DBMS=CSV
- B. REPLACE-YES
- C. GUESSINGROWS=MAX
- D. OUT=dataset
- E. MISSING-YES
Answer: E
Explanation:
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.
NEW QUESTION # 244
You have a SAS dataset named 'CUSTOMERS' with variables 'CustomerlD', 'Name', 'City', 'State', and 'Zipcode'. You want to create a report that displays only the 'CustomerlD', 'Name', and 'City' variables for customers residing in 'California' and 'Texas' but not in 'Los Angeles' city. Which PROC PRINT statement achieves this?
- A.
- B.
- C.
- D.
- E.
Answer: C
Explanation:
The correct answer is option A. The 'WHERE statement filters the data to include customers with 'State' values 'California' or 'Texas' and excludes customers with 'City' value 'Los Angeles'- This ensures the report only displays customers in 'California' and 'Texas' except those in 'Los Angeles'. Option B includes customers only in 'Los Angeles' Options C, D, and E do not include customers residing in 'Texas' or do not exclude customers from 'Los Angeles' city.
NEW QUESTION # 245
Consider a dataset 'Sales' with variables 'Region', 'Product', and 'Sales_Amount'. You need to create a new dataset 'Summary' that reports the total sales for each region and product combination, but only for regions where the total sales exceed $10,000. Which SAS code would you use to achieve this?
- A.
- B.
- C.
- D.
- E.
Answer: D
Explanation:
The correct answer is E. The code uses the BY statement to group the sales data by Region and Product. The function calculates the total sales for each group. The OUTPUT statement is then executed only if the sum is greater than 10,000, effectively filtering out regions with total sales below this threshold. Options A and B are incorrect because they do not use the correct function to calculate the total sales for each region-product combination. Option C is incorrect because it only checks for the last record in each region. Option D is incorrect because it only checks for the first record in each region. This scenario demonstrates how to use the OUTPUT statement in conjunction with BY group processing and aggregate functions to create a summary dataset based on specific conditions. It requires understanding the correct function and the use of group processing for data aggregation.
NEW QUESTION # 246
......
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