Survey Sampling

In the context of an SQL interview, when asked about "Survey Sampling", the interviewers are looking to understand your knowledge and experience with the process of selecting a subset of data or observations from your database which can provide insights into the whole data set. This is a commonly used method when working with large datasets, which can be time-consuming and resource-intensive to process entirely.

Key points to focus in your answer might be:

• Demonstrating how to use SQL to take a sample from a larger dataset.
• Knowing when and why you would want to take a sample.
• Being aware of different strategies for sampling, like random sampling or stratified sampling.

One of the ways to perform survey sampling in SQL is to use the RAND function. This can be used to take a random sample of rows from a larger dataset. Here is a simple example on how to select 100 random rows from a table:

SELECT * 
FROM Table1
ORDER BY RAND() 
LIMIT 100;

In this example, RAND() generates a random value for each row in the table, ORDER BY RAND() sorts these random values, and then LIMIT 100 selects the first 100 of these sorted rows. This results in a random sample of 100 rows from the table.

Another way to implement survey sampling in SQL is using the TABLESAMPLE clause (in SQL servers that support it). TABLESAMPLE retrieves a pseudo-random sample of data from a table. For instance, if we want to get a 10 percent random sample of the rows in a table, you can use the following query:

SELECT *
FROM Table2 TABLESAMPLE (10 PERCENT);

This method ensures that the data returned represents an unbiased sample from the table, however, the actual percentage of rows returned can be somewhat less or more than expected. Hence, for true accuracy, it's best to use the RAND() method.