Probability:
Two approaches to interpret probability include thefrequentistapproach or theBayesian approach. To be perfectly honest before writing this discussion post I had no clue what these two statistical methods were referring to. I now know that thefrequentistapproach focuses on the probability of the data given the hypothesis, and TheBayesianapproach is the opposite. This method focuses on the probability of the hypothesis given the data (Fox, 2011). After reading about both approaches one thing is certain, both thefrequentistandBayesianprobabilities must satisfy the same algebraic rules to be statistically valid (Ambaum, 2012). I can view both sides. I agree with thefrequentistlogic that “the more data we collect, the better we can pinpoint the truth (Ambaum, 2012).” I also agree with theBayesianapproach which allows previous beliefs to be interpreted when observing data. Overall, I feel I am not familiar enough with both approaches to make a stance on which interpretation would be superior over the other. I must admit though it is pretty amusing reading people get so worked up over which method reigns supreme.
In the blog we read this week the author says “a lot of people frequently misunderstand how to apply statistics: they’ll take a study showing that, say, 10 out of 100 smokers will develop cancer, and assume that it means that for a specific smoker, there’s a 10% chance that they’ll develop cancer. That’s not true (Chu-Carroll, 2008).” I agree with the author. Just because there is a 10% chance that 10 out of 100 smokers will develop cancer does not mean that the smoker will indeed get cancer. There is never a sure way of knowing.
I took statistics a decade ago, so my memories are vague. I do remember attempting to learn about “p values” and “z-scores” in a noisy lecture hall at Clemson University. Learning biostatistics from home is a nice change of pace. It is pleasant to have a quiet place to focus, because sometimes I have a difficult time setting up probability problems. If I am not careful I can get confused and read the question wrong. Needless to say if you set the arithmetic up wrong then the probabilities you are trying to calculate will be wrong. I think Benoit Mandelbrot describes probability best when he said, “The theory of probability is the only mathematical tool available to help map the unknown and the uncontrollable. It is fortunate that this tool, while tricky, is extraordinarily powerful and convenient.”
References
Chu-Carroll, M. (2008, April 7).Schools of thought in Probability Theory. Retrieved from Science Blogs:
Fox, J. (2011, October 11).Frequentist vs. Bayesian. Retrieved from Oikos:
Ambaum, M. (2012).Frequentistvs Bayesian statistics—a non-statisticians view Retrieved from: