Uninformative prior

Alright kiddo, so imagine you have a box of candies but you have no idea what flavor they are. You have no information about the candies at all! This is what we call having an "uninformative" prior.

In statistics, prior information is everything we know about a situation before we start collecting data. An uninformative prior means that we don't have any previous information to guide us, just like having no idea about the flavors of the candies.

To help us figure out what flavors the candies are, we need to collect some data by tasting them. As we start to taste them, we will get some new information about the flavors. This is called the "posterior" information.

Now, if we had some information about the flavors of the candies before we tasted them, we could use it to guide our tasting process. For example, if someone told us that the box contains only fruity candies, we would be more likely to guess flavors like strawberry or grape instead of chocolate or mint.

But if we have no prior information, every flavor is equally likely and we have to rely solely on the data we collect by tasting the candies. This is what we call an "uninformative" prior.

So, an uninformative prior is like having no idea about something and having to rely only on new information we gather to make decisions. It's like starting from scratch and having no opinions or biases to guide us.