## Monday, April 11, 2016

### Find some way for statistics to prove it

One of scientific research main challenges include the lack of experimental design and execution which meet a significant testing procedure. I myself have experienced these types of issues arise in my own laboratory experience. One of the first warning signs of the issues was that the experimental design never followed the null hypothesis significance testing procedure. A common day in the lab would consist of designing an experiment that included the appropriate controls, instead of designing an experiment based on what type of statistical test would need to be performed (t-test, ANOVA). Secondly, one should form an if/then statement that contains the statistical null and the alternate hypothesis based on predicted effect. In addition, alpha and beta threshold errors were not considered prior to an experimental design, well –up until the beginning of this course this was not been done. It seems that as a young scientist I had never heard of the concept of designing an experiment where the sample size, exclusion criteria was planned out prior to the execution of the experiment. It was truly shocking and unfortunate to find out in a class that I had been doing this wrong the whole time. I was just like the scientist described in the comic below. Finding a way to use statistics to prove something I had preconceived in my mind as being correct.

One of the major challenges in statistics is the lack of knowledge of the appropriate set up of an experiment. This may be due to the complex language that is used like, error threshold, explanatory groups, degrees of freedom. Which to us now appear as a second language, where once words we did not truly understand. I think most importantly is the issue of not knowing when to begin thinking of statistics in our research. Now it is ingrained in our brains, we must determine the type of data we are acquiring to determine the test we will perform. However, just last year I was collecting data, analyzing it and call it a day.

In order to overcome of the major challenges in statistics, we need to educate scientist early in their careers. Requiring these type of course as part of the grants that professors take, or as a department graduation requirement. I know in my case; this was an elective. Cannot image what my final PhD work would be like if I did not know what I know today.