My dad, Gabriel Ben-Gan, passed away recently. He loved numbers, logic and puzzles, and used to solve problems in his own unique way. This article is about a puzzle that incorporates the above ingredients. Dad, this one’s for you, and is in your memory.
In one of my previous blogs I explained basic descriptive statistics procedures. When you prepare the data for Data Mining, there is never enough of over viewing and checking the data with statistical methods. Therefore, it would be nice to have more of them available in SQL Server. Very useful measures are the 3rd and the 4th population moments- Skewness and Kurtosis.
I wrote two blogs about Skewness and Kurtosis, one with T-SQL and one with C# UDA solution. I claimed the CLR solution performs better, because it needs only one pass through the data, and the T-SQL one needs two passes. This is correct, considering my solutions, the CLR one is twice as fast as the T_SQL one. But…
Seems like this is quite interesting topic, I have another extremely valuable comment. Joe Celko – I really don’t think his name needs any introduction hereJ – sent me another suggestion for an improvement of Steve’s version – use the standard POWER() function to return the Age column to a specific power instead of calculating the value manually.
As being the guest author on Itzik Ben Gan’s Inside MS SQL Server 2005: T-SQL Querying book, this blog might seem boasting to you. However, I did not write anything in the chapter 9 – Graphs, Trees, Hierarchies and Recursive Queries, and I am talking about this chapter. In a single day, I used the following solutions from the chapter: