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### Q: what book on Bayesian statistics, preferably with R? [duplicate]

I am frequentist by training and practice, but I'd like to learn more about Bayesian statistics. I know the basics, but I would be at a loss if I had to, for example, replace my normal ANOVA ...
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### Book Bayesian statistics [duplicate]

I write here to ask for a suggestion about a graduate level Bayesian statistics book. I have a bachelor degree in statistics but despite having a fairly solid background on frequentist and non ...
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### Recommendations for learning probability and Bayesian statistics? [duplicate]

I have been very interested lately in learning Bayesian Statistics, but I have only a little bit of background in the frequentist statistics, only one term at University. Some of the books that I ...
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### How did you learn Bayesian statistics and what would you recommend as a reliable source? [duplicate]

I'm running a Bayesian model and I'm stuck on some aspect of the model that I have difficulty to understand. Since my knowledge about Bayesian inference is limited, I would like to have some good ...
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### Bayesian references [duplicate]

Any good places to start getting into Bayesian statistics? I'm a graduate student in social sciences, with a decent amount of stats classes under my belt, but I'm far from fluent. Any references would ...
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### recommended books for preliminary concepts of Bayesian Statistics [duplicate]

I am interested in learning Bayesian Statistics related for my CS career. I have a very little background on frequentist statistics, which I know differs from the bayesian approach. The reason of my ...
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### What is a good book about the philosophy behind Bayesian thinking?

What is a good book about Bayesian philosophy, contrasting subjectivists against objectivists, explaining the view of probability as state of knowledge in Bayesian statistics, etc.? Maybe Savage's ...
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### Checking whether accuracy improvement is significant

Suppose I have an algorithm that classifies things into two categories. I can measure the accuracy of the algorithm on say 1000 test things -- suppose 80% of the things are classified correctly. Lets ...
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### Use of prior and posterior predictive distributions?

I understand the prior and posterior distributions and I have read what the prior and posterior predictive distributions are. However, I don't really see the point of knowing them. Knowing more ...
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### Which expansions and identities are useful to applied statisticians? [closed]

Simple mathematical relationships like $V(X) = E(X^2) - E(X)^2$, aside from being theoretical results, are useful because they allow analysts to do back-of-the-envelope calculations, restate results ...
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### “Bayesian and Frequentist Regression Methods” by Jon Wakefield, a good introductory Bayesian textbook for frequentist economics graduates?

Here's a link to a good question regarding Textbooks on Bayesian statistics from some time ago. People suggested John Kruschke's "Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS"...
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### Composition of probability density

I know probability distribution for parameter $\phi$. I have the empirical distribution/statistical distribution of $X$ that is dependent on parameter $\phi$ for $\phi \in [0,1]$. I assimilate this ...
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### Bayesian analysis: Estimate whether a parameter is 0 or not

I have the following problem: I need to assess whether a given parameter $B$ is equal to 0. Let's consider the following model (my problem is more complicated but I think that this example is ...
My question is about how to actually do this both rigorously and practically. Allow me to elaborate. Suppose that we have data $(x_1,y_1),...,(x_N,y_N) \in \mathbb{R}^p \times \{0,...,k-1 \}$. I'd ...