Expected value of sample information
Ok kiddo, so let me explain what the "expected value of sample information" means. Do you remember when we go on a treasure hunt and we have a map that shows us where the treasure might be hidden?
Now, let's say we have a big jar filled with jellybeans and we want to guess how many jellybeans are in it. But we don't want to just guess randomly, we want to use some information to make a better guess. So, we decide to take a small sample of jellybeans out of the jar and count them. For example, we might take out 10 jellybeans and count them.
After counting, we can use that information to make a better guess about how many jellybeans are in the jar. But we're still not 100% sure and we might be willing to take more jellybeans out of the jar to count them and get even more information.
Now, the "expected value of sample information" is a fancy way of saying that we're trying to figure out if taking more jellybeans out and counting them is actually worth it. We want to know how much better our guess will be if we take more jellybeans out and count them.
So, we do some calculations to figure out if it's worth taking more samples. We look at how much it costs to take another sample (like our time to count them) and how much better our guess can be if we do take more samples. If the cost of taking another sample is less than how much better our guess can be, then it's worth it to take another sample.
And that's basically what the "expected value of sample information" means! It's just a way to figure out if taking more samples to get more information is worth it or not.
Now, let's say we have a big jar filled with jellybeans and we want to guess how many jellybeans are in it. But we don't want to just guess randomly, we want to use some information to make a better guess. So, we decide to take a small sample of jellybeans out of the jar and count them. For example, we might take out 10 jellybeans and count them.
After counting, we can use that information to make a better guess about how many jellybeans are in the jar. But we're still not 100% sure and we might be willing to take more jellybeans out of the jar to count them and get even more information.
Now, the "expected value of sample information" is a fancy way of saying that we're trying to figure out if taking more jellybeans out and counting them is actually worth it. We want to know how much better our guess will be if we take more jellybeans out and count them.
So, we do some calculations to figure out if it's worth taking more samples. We look at how much it costs to take another sample (like our time to count them) and how much better our guess can be if we do take more samples. If the cost of taking another sample is less than how much better our guess can be, then it's worth it to take another sample.
And that's basically what the "expected value of sample information" means! It's just a way to figure out if taking more samples to get more information is worth it or not.
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