- Thread starter javedbtk
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- Tags bayes statistical analisys

Step one. What is the distribution of the data, i.e. what is the likelihood?

(Btw Bayesian)

(Btw Bayesian)

Let's say, algorithm A has data like, 0.01, 0.15, 0.03, - 0.21

What is the sample size?

If you intended to use Bayes theorem you would need to have the likelihood and a prior distribution. And by that I mean the densities from a distribution, like e.g. the gamma distribution.

I guess that the data are non-negative, are close to zero and that the data are skewed. I would look at distributions like the gamma distribution or the log-normal distribution. Then you could do maximum likelihood estimate of that and test if the means are equal.

What is the sample size?

I guess that the data are non-negative, are close to zero and that the data are skewed. I would look at distributions like the gamma distribution or the log-normal distribution. Then you could do maximum likelihood estimate of that and test if the means are equal.

What is the sample size?

If you take the log of the data (for each of the two groups) what does the histogram like then? Does it look like the normaldistribution (i.e. bell shaped)?

Are the data such that it must be larger than zero? (i.e. non-negative)

Are the data resticted to be between zero and one (between 0 and 1)?

What is your familiarity with Bayesian analyses?

If you take the log of the data (for each of the two groups) what does the histogram like then? Does it look like the normaldistribution (i.e. bell shaped)?

Are the data such that it must be larger than zero? (i.e. non-negative)

Are the data resticted to be between zero and one (between 0 and 1)?

So the data is between -1 and +1. (Is it correlations?)

What does the historgam look like?

if the sample size is about n=500 in each group, why not just rely on the central limit theorem and compare the means and do a z-test? What are the means, standard deviation and n1 and n2?

So the data is between -1 and +1. (Is it correlations?)

What does the historgam look like?

if the sample size is about n=500 in each group, why not just rely on the central limit theorem and compare the means and do a z-test? What are the means, standard deviation and n1 and n2?

Now I need a statistical test which is not frequentist because I read that frequentist tests are biased.

Don't get me wrong... I love Bayesian methods but this seems silly.

Don't get me wrong... I love Bayesian methods but this seems silly.

I am also interested in why @javedbtk wanted to go the Bayesian way. And I want to hear her/his answer.

(@javedbtk: @Dason knows a lot about Bayesian analysis. Please listen to him. And please explain to us all about how you think about things.)