Eleni Markou explains what window functions are:
What we want is a table with an extra column which will represent the average price of all products belonging to the same category as the one on the current line.
One approach to solve this problem is to calculate the average price per category using an aggregate function and then join the result with the initial table over the Product Type column in order to get a new table looking at which you can easily find out if a product is more expensive than the average of its category.
Although this would definitely do the job, the query would be quite complicated and lengthy and may lack readability. To avoid these, an alternative approach would be to make use of window function where there is no need to mess with subqueries and joins. When using a windowed function, you can retrieve both aggregated and non-aggregated values at the same time while when using GROUP BY you can get only the results grouped into a single output row.
I ask questions about window (or windowing) functions whenever I interview someone for a job. They are extremely useful things, and I highly recommend Itzik Ben-Gan’s windowing functions book for SQL Server 2012 if you want to learn a lot more.