Statistics

           The last statistics class I took was AP Stats in my senior year of high school. The AP credit I entered UMass with satisfied my biology major statistics requirement. However, statistics have come up in many of the other classes I have taken at UMass. I remember my high school teacher saying there were two categories of statistics, which were exploratory and inferential. Exploratory statistics was for describing variables, and included things like mean, median, mode, variance, and standard deviation. Inferential statistics was for finding differences or relationships between variables, and involved things like t-tests and chi-square. I remember t-tests and chi-square involved p values. I’m pretty sure p values represent the probability of getting whatever results you observed if the null hypothesis is true, with the null hypothesis being that there is no difference or relationship among whatever variables you’re testing. The conventional p value is 0.05, representing a 95% confidence that you can reject the null. However, in my Genomics and Bioinformatics class that I am taking this semester, my professor made the distinction between statistical significance and biological significance by explaining that some results may not conform to the 0.05 p value, but that does not necessarily mean they should be disregarded, because the 0.05 p value is only convention and does not represent some mathematical absolute. She said that depending on the research question, the 0.05 p value may not be valuable. I also remember there are type one and type two errors that can come up related to the null hypothesis. One of the errors involves rejecting the null when the null is true, and the other involves accepting the null when the null is false, but I don’t remember which is which.