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==Bayesian Approaches==

==Bayesian Approaches==

[[Bayesian statistics]] is a method of applying [[Bayes equation]] to data analysis. One of the biggest difference between Bayesian approaches and frequentist approaches is that Bayesians attempt to determine the probability that a given hypothesis is true given the data, while frequentist attempt to define the probability of getting the data given that a particular hypothesis is true.  

[[Bayesian inference | Bayesian statistics]] is a method of applying [[Bayes equation]] to data analysis. One of the biggest difference between Bayesian approaches and frequentist approaches is that Bayesians attempt to determine the probability that a given hypothesis is true given the data, while frequentist attempt to define the probability of getting the data given that a particular hypothesis is true.  

Bayesian approaches are becoming more and more popular in science because what most people are interested in is the probability of proposed hypothesis no the probability of the data. It also does not need to make prior assumptions about the data such as [[Normal distribution | normality]] and [[homogeneity of variance]]. However, Bayesian methods have come under fire from many frequentist proponents. There is actually a very heated debate in statistical circles about the respective validity of both methods. The primary complaint leveled at Bayesian statistics is that it must use a [[prior probability]] of a hypothesis in its analysis. Often this prior is not known out right and assigned seemingly arbitrary values based on particular distributions such as the [[uniform distribution]] or [[beta distribution]].   

Bayesian approaches are becoming more and more popular in science because what most people are interested in is the probability of proposed hypothesis no the probability of the data. It also does not need to make prior assumptions about the data such as [[Normal distribution | normality]] and [[homogeneity of variance]]. However, Bayesian methods have come under fire from many frequentist proponents. There is actually a very heated debate in statistical circles about the respective validity of both methods. The primary complaint leveled at Bayesian statistics is that it must use a [[prior probability]] of a hypothesis in its analysis. Often this prior is not known out right and assigned seemingly arbitrary values based on particular distributions such as the [[uniform distribution]] or [[beta distribution]].