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Now, I should say if we got this, you don't find any immediate
significant about statistics and probability.
This is totally nontrivial, but it comes in very handy.
So, I'm going to practice this with you using a second example. In this case, you are a robot.
This robot lives in a world of exactly two places. There is a red place and a green place, R and G.
Now, I say initially, this robot has no clue where it is,
so the prior probability for either place, red or green, is 0.5.
It also has a sensor as it can see through its eyes, but his sensor seems to be somewhat unreliable.
So, the probability of seeing red at the red grid cell is 0.8,
and the probability of seeing green at the green cell is also 0.8.
Now, I suppose the robot sees red.
What are now the posterior probabilities that the robot is at the red cell given that it just saw red
and conversely what's the probability that it's at the green cell even though it saw red.
Now, you can apply Bayes Rule and figure that out.