Welcome once again to the fetid den of iniquity that is my blog-post, dear readers. As I mentioned last week, I have been conducting analyses on my second experiment, and progress could be called 'rocky'.
Well, if last week was rocky, it is now firmly ensconced in the Himalayas. Initially, I had performed an analysis of my data while eliminating outliers above and below certain thresholds across all participants and conditions. Statistical significance was achieved after this cleaning was done. However, based on previous research we also deleted outliers based on standard deviations of each participant. Statistical significance vanished.
Now, understand that before all this, I had forgotten to perform some of the most basic and elementary forms of data cleaning known to psychology before doing an analysis. I was feeling like a bit of a fool.
It transpired that certain participants had data that did not make the slightest bit of sense; reaction times that were unfeasible, etc, and were placing rather large spanners in the works of the data. Being the overenthusiastic (and also perhaps cerebrally-challenged) lad that I was, I had not noticed this. My supervisor did, and drew it to my attention. Having received this information, I proceeded to pummel my own head into nearby solid objects located in my office. To forget to deal with outliers, AND to forget to observe individual means (a lesson I was taught in no uncertain terms by my Honours supervisor) is an impressive brain failure, I thought. As a quick aside, I am my own worst critic when it comes to my career. These days, I am unforgiving (perhaps to a fault) when it comes to mistakes such as the aforementioned.
Generally I avoid directly giving advice in this blog, as I prefer people to take whatever insight they wish from the posts (e.g. "why are they allowing this coffee-addicted nutcase into the sunlight?"). However, I will say this; it's not in your interest to be an unforgiving disciplinarian when you make mistakes. The PhD learning curve is a steep one, and if you continue in academia it apparently doesn't shallow out that often. Mentally injuring yourself simply hamstrings your ability to learn from your mistakes. It's also why your supervisor is there; they're good at this stuff. My supervisor has been in academia for almost two decades. I have been a PhD student for 8 months. When I took the data to him, he saw the problem after a few minutes of perusal and basic analysis. Go figure.
The outcome of all this is that I must return to testing, both replacing the faulty data (and finding out how it happened) and expanding the sample size. The rest of the week is filled with testing schedules and importing the new data. Lessons have been learned, shoulders squared, heads un-pummeled and egos deflated (at least a little . . . :D), and the science goes on! See you next week, when hopefully I have new results to speak of!