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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q122-Q127):

NEW QUESTION # 122
You have a SAS dataset named 'SALES' with a variable 'REGION' that contains region codes. You want to generate a report that displays the region codes as 'East Coast', 'West Coast', 'Midwest', and 'South' based on their corresponding numeric values. Which code snippet correctly uses the LABEL statement to achieve this?

Answer: B

Explanation:
The LABEL statement is used to define temporary attributes for variables- In this case, it assigns labels to specific values of the 'REGION' variable, which will be used in the report output Option E uses the correct syntax for assigning multiple labels to different values within the 'REGION' variable. The other options contain syntax errors or use incorrect approaches for defining labels.

NEW QUESTION # 123
You have a SAS dataset named 'SALES with variables 'Region', 'Product', and 'Sales'. You want to create a new dataset 'SALES SUMMARY' that summarizes sales by region and product. Which SAS code snippet correctly performs this task, assuming that the 'Sales' variable is numeric and the 'Region' and 'Product' variables are character? Choose all correct options.

Answer: A,B,D

Explanation:
The correct code snippets are A, B, and D. Option A uses PROC SQL to create the summary dataset. Option B uses PROC SUMMARY to calculate the sum of sales for each combination of Region and Product. Option D uses PROC MEANS to perform the same calculation as PROC SUMMARY. Option C is incorrect because it does not correctly calculate the sum of sales for each group. Option E is incorrect because it attempts to calculate the sum of sales only for the last observation of each group.

NEW QUESTION # 124
You have a SAS dataset called 'SALES' with variables: 'Region', 'Product', 'Sales_Amount', 'Date', 'CustomerlD'. You need to create a new dataset called 'SALES SUMMARY' that contains only the variables 'Region', 'Product', and 'Sales_Amount' for observations where 'Sales_Amount' is greater than 1000. Which code snippet correctly achieves this?

Answer: C

Explanation:
The correct answer is "B". It uses a 'keep' statement to specify the desired variables ('Region', 'Product, 'Sales_Amount') and an 'if statement to filter observations where 'Sales_Amount' is greater than 1000. This code ensures only the relevant data is included in the new dataset 'SALES_SUMMARY'. Option A is incorrect because the 'drop' statement removes variables after the data is filtered, not before, resulting in unwanted variables in the output. Option C is incorrect because it uses 'keep' before the 'if statement, which will include all observations, not just the ones with 'Sales_Amount' greater than 1000. Options D and E are incorrect because they lack an 'output' statement, meaning no observations will be written to the new dataset.

NEW QUESTION # 125
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: D

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 # 126
You are analyzing a dataset containing customer purchase dat
a. You need to create a frequency report that shows the number of customers who made purchases in each month. You need to suppress the cumulative frequencies and percentages, but you want to see the percentage of customers who purchased in each month relative to the total number of customers. Which PROC FREQ statement achieves this?

Answer: E

Explanation:
The correct answer is B. The 'NOCIJM' and 'NOPERCENT options suppress cumulative frequencies and percentages. The 'OUTPCT option calculates the percentage of observations in each category relative to the total number of observations, which is what you need to show the percentage of customers who purchased in each month. Option A does not calculate the percentage of customers. Option D does not provide the percentage of customers. Options C and E do not provide the percentage of customers. The options C and E would not provide the desired output.

NEW QUESTION # 127
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