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[[Bayesian inference|Bayesian statistics]] is a method of applying [[Bayes theorem]] 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 theorem]] 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 the proposed hypothesis, not 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. This has led to very heated debate in statistical circles, though this has largely died now, 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. This prior is intended to build contextual information into the analysis, but it may be seen by its critics as subjective or arbitrary.  Commonly used prior distributions include the [[uniform distribution]] and [[beta distribution]].   

Bayesian approaches are becoming more and more popular in science because what most people are interested in is the probability of the proposed hypothesis, not 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. This has led to very heated debate in statistical circles, though this has largely died now, 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. This prior is intended to build contextual information into the analysis, but it may be seen by its critics as [[Subjectivism|subjective]] or arbitrary.  Commonly used prior distributions include the [[uniform distribution]] and [[beta distribution]].   

===Descriptive statistics===

===Descriptive statistics===