First of all, if your research progress is slowed by fear of statistics, your are certainly not alone. Being afraid to "mess-up" your stats, and thus your project, is a common lament. But I'm here to tell you that your project is not that fragile! Once your data is collected, entered, cleaned, and ready for analysis, it is time for excitement, not concern! The golden rule here is: BACK UP.…
First of all, if your research progress is slowed by fear of statistics, your are certainly not alone. Being afraid to "mess-up" your stats, and thus your project, is a common lament. But I'm here to tell you that your project is not that fragile! Once your data is collected, entered, cleaned, and ready for analysis, it is time for excitement, not concern! The golden rule here is: BACK UP.…
Warning, this blog will be short, sweet, and a bit pithy. The two most common questions that I receive about statistical analyses, no matter what kind or purpose, is: "Am I doing it right?" or "Am I allowed to...(fill-in a variation of a common analysis here)?" My response to these questions is usually: "Sure, you can do whatever you want, but what will it mean if you do?" I've said…
Anyone that has taken a statistics class has probably learned about transforming data, at one time or another (although you may be in denial about it). In short, you may want to transform your data if you need to perform a parametric analysis, but the inherent assumptions are violated in your dataset. While this seems simple enough, many researchers are hesitant to employ this tactic of handling non-normally distributed data.…
