At least once a month I use an INDEX/MATCH formula to match and merge patient data from multiple Excel files. I wrote this post because when I first sought to learn the technique I found the other tutorials on the web either lacking or hard-to-follow.
This is not another article explaining various missing data techniques. This is a post about how to use them without getting an advanced degree in statistics or charming that nice young Data Analyst into doing it for you.
Recently I had to provide a script to convert a dataset of raw assessment scores into an Oracle table with the scores ordered by percentile rank. This is a common request so I figured a short, non-technical post on percentile ranking might be helpful to a lot of people.
There are three main ways to calculate percentile ranks in Oracle 9i or later:
(a) Calculate them manually with Joins and Sub-queries;
(b) Use the CUME_DIST function and format the results as a percentage;
(c) Use the PERCENT_RANK function.
In this post I’m going to focus on options (b) and (c) because the only people who would reinvent the wheel and use (a) are SQL programmers who don’t know (b) and (c) already exist.