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SASInstitute A00-215 Latest Braindumps Questions - A00-215 High Passing Score

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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q274-Q279):

NEW QUESTION # 274
You are tasked with analyzing a dataset where the date variable 'TransactionDate' is stored as a numeric value representing the number of days since January 1, 1960. You need to display the date in the format 'MMDDYYI 0.' Which SAS code snippet accomplishes this task correctly?

Answer: C

Explanation:
The correct answer is ''E''. To format a SAS date value, you need to use the 'input' function to convert the numeric value to a SAS date and then apply the desired format using the 'format' statement. Option E uses the ' input' function with the 'DATE9.' format to convert the numeric value to a SAS date and then applies the 'MMDDYYIO.S format to display the date in the desired format. Option A would only apply the format to the variable but would not convert the numeric value to a date. Option B tries to use the 'put' function, which is used to convert a SAS date to a character string, but does not convert the numeric value to a date first. Option C uses the 'date' function, which expects a string representation of the date and does not work with numeric date values. Option D uses the 'input' function but with the wrong format, which would result in an incorrect date conversion.

NEW QUESTION # 275
You have a SAS dataset named 'SALES' with variables 'REGION', 'PRODUCT', and 'SALES AMOUNT'. You need to generate a report that displays the total sales amount for each region, but only for products with a sales amount greater than $10,000. Which PROC PRINT statement achieves this, incorporating the LABEL option for clarity and the NOOBS option to suppress observation numbers?

Answer: B

Explanation:
The correct answer is option C. This code snippet uses the WHERE clause to filter for sales amounts greater than $10,000- The SUM statement then calculates the total sales amount by region, and the LABEL option assigns a descriptive label to the 'REGION' variable. The NOOBS option suppresses the observation numbers in the output- Options A, B, D, and E contain errors or missing elements. A filters but doesn't aggregate, B aggregates but doesn't filter, D has an incorrect label placement, and E lacks the NOOBS option- Only option C successfully incorporates all necessary elements for the desired report

NEW QUESTION # 276
Given the input data set WORK. GR_ANS with two character variables:

The following SAS program is submitted:

Which report is created?
A)

A. Option A
B. Option C
C. Option D
D. Option B

Answer: C

NEW QUESTION # 277
You have a dataset 'sales_data' with variables 'Region', 'Product', and 'Sales'. You want to create a frequencyreport that displays the frequency counts for each region and product combination, but you only want to see the counts for those combinations where the sales value is greater than $10,000. How would you modify the PROC FREQ statement to achieve this?

Answer: B

Explanation:
The 'where' statement is used to filter the data before the frequency analysis. It specifies a condition (sales > 10000) to include only those observations that meet the specified criteria. Option B uses 'if statement which is not valid in PROC FREQ. Option C is incorrect as the WHERE statement is not used correctly and would not filter the data. Option D uses the 'select if statement which is not valid in PROC FREQ. Option E is incorrect as it uses the 'gt- operator which is not valid in this context.

NEW QUESTION # 278
You have a SAS dataset 'PRODUCT SALES' with variables 'PRODUCT ID', 'SALES DATE', 'QUANTITY SOLD', and PRICE'. You need to create a new dataset 'MONTHLY SALES' that only includes observations where 'SALES DATE' falls within the month of June (regardless of year) and the 'PRICE' is greater than 100. Which code snippet would you use to achieve this?

Answer: C

Explanation:
The correct code snippet is option B. It utilizes the 'month' function to extract the month from the 'SALES_DATE' variable and compares it to 6 (June). Additionally, it incorporates the 'PRICE' condition, ensuring only observations with 'PRICE' greater than 100 are included in the new dataset 'MONTHLY_SALES'. Option A only filters by month, neglecting the price criterion. Option C filters for a price less than 100, which contradicts the requirement. Option D attempts to compare the 'SALES DATE' variable to a string 'June', which is incorrect syntax. Option E only filters by month and lacks the 'then' statement for outputting to the new dataset.

NEW QUESTION # 279
......

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