Skip to main content
Cross Validated

Return to Question

Post Reopened by mkt, jbowman, mdewey, Silverfish, whuber♦
Post Closed as "Needs details or clarity" by Michael R. Chernick, kjetil b halvorsen♦, Peter Flom
edited body; edited tags; edited title
Source Link
Xi'an
Xi'an
  • 107.7k
  • 13
  • 190
  • 676

what does p( y | μ,σ2σ²) really mean?

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2σ²) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it - I am too stupid for that :) )

what does p( y | μ,σ2) really mean?

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it - I am too stupid for that :) )

what does p( y | μ,σ²) really mean?

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ²) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it - I am too stupid for that :) )

added 31 characters in body
Source Link
Sachar Rosen
Sachar Rosen
  • 51
  • 4

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it - I am too stupid for that :) )

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it)

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it - I am too stupid for that :) )

Source Link
Sachar Rosen
Sachar Rosen
  • 51
  • 4

what does p( y | μ,σ2) really mean?

Just started to study Bayesian Statistics. I am very confused the concept of having a conditional probability on a distribution. Specifically:

I understand what p( A | B ) where A="I am sick" and B = "Took a flu shot" means. (probability that I am sick, given that I am from the probability of the population that took a flue shot)

But what does p( y | μ,σ2) mean?

Can an example be provided? (Just the term "y given a normal distribution" won't help me understand it)