The derivation of the expected value can be found here. 1, p) # Toss a coin and add to 'head' counter to 'counter' }. Okay. Let's see. X is the count of tosses until the first head. This is a random variable of some distribution. I wonder what? We have that. It is important to understand that " expected value " is not same as "most probable What is the expected number of coin flips for getting two consecutive heads?.
We can also imagine situations where we don't actually look at data we collect, but try to anticipate what data would like if we collected it. Here is what I think: Here's how it works: The second part of this equation considers the average squared deviation from the mean expected in any given trial. Here's how it works: Rational agents may have good reasons to do something else!
Expected value coin toss Video
Expected value coin toss - freue
If it lands tails up, I get nothing. The expected value is center of the hypothetical sampling distribution, so it a mean. SE's are the square root of the average of the squared deviations from the expected value, where in this case it is the expected value of the net gain. You may also want to take a look at my answer, which some people call "first-step analysis". From my understanding, x is the "additional" expected number in the drawing tickets game, which is a different game from the original game, beacause the expectation let me call it "E" of the coin game includes the first tossing. Here's how it works: Imagine you flipped a fair coin twice to count the number of heads.