SAS Interview Questions and Answers for experienced

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100 SAS Interview Questions and Answers

  1. What are the different types of SAS data sets?

    • Answer: SAS supports several data set types, including: Observation data sets (the most common, storing data in rows and columns), Library (collection of data sets), Engine (in-memory data set), View (dynamic data set that references another data set), and more specialized formats like formatted data sets. The choice depends on the specific task and efficiency needs.

  2. Explain the difference between PROC SQL and DATA step.

    • Answer: PROC SQL uses SQL syntax to manipulate data, offering a more declarative approach. DATA step is a procedural language; you explicitly define the steps to process data. PROC SQL is often faster for large datasets and set operations, while DATA steps provide more control over individual data manipulations. The best choice depends on the task's complexity and the data size.

  3. How do you handle missing values in SAS?

    • Answer: SAS represents missing values with special characters (e.g., ".", " ."). You can handle them using techniques like: Replacing missing values with a specific value (e.g., mean, median, or zero), using conditional logic to exclude records with missing values, imputing missing values with statistical methods (PROC MI), or flagging missing values for subsequent analysis.

  4. What are the different types of joins in SAS?

    • Answer: SAS supports various joins, including INNER JOIN (returns only matching records from both tables), LEFT JOIN (returns all records from the left table and matching records from the right), RIGHT JOIN (returns all records from the right table and matching records from the left), and FULL JOIN (returns all records from both tables). Understanding these is crucial for merging and relational data manipulation.

  5. Explain the concept of macros in SAS.

    • Answer: Macros are essentially reusable blocks of SAS code. They enable automation and modularity. You define a macro with parameters, then invoke it multiple times with different values. This makes code more efficient and easier to maintain. They are particularly useful for repetitive tasks or when you need to generate code dynamically.

  6. How do you perform data validation in SAS?

    • Answer: Data validation involves checking data quality. In SAS, you can use techniques like: Data checks (e.g., verifying ranges, data types, and formats), using the `IF-THEN-ELSE` statements to flag incorrect values, frequency checks (PROC FREQ), and generating summary statistics to identify outliers. PROC VALIDATEDATA is a specific procedure dedicated to data validation.

  7. What are some common SAS functions for string manipulation?

    • Answer: Common string functions include: `UPCASE`, `LOWCASE` (convert to uppercase or lowercase), `LENGTH` (returns string length), `SUBSTR` (extract a substring), `INDEX` (find a substring's position), `TRIM` (remove leading/trailing spaces), `COMPRESS` (remove specific characters), and `TRANSLATE` (replace characters).

  8. Describe your experience with SAS procedures for statistical analysis.

    • Answer: (This requires a personalized answer based on experience. Mention specific procedures like PROC MEANS, PROC REG, PROC GLM, PROC ANOVA, PROC CORR, PROC FREQ, PROC CATMOD, PROC MIXED, and describe the types of analyses you've performed with them, mentioning any advanced statistical techniques used.)

  9. How do you create a SAS report?

    • Answer: SAS reports can be created using various methods: PROC PRINT (basic reporting), PROC REPORT (more sophisticated formatting), PROC TEMPLATE (highly customizable reports), and using ODS (Output Delivery System) to export reports in various formats (PDF, HTML, RTF).

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