![PPT8[Probability]](http://s1.studyres.com/store/data/008680376_1-83662e321d4099834200546219a133a1-300x300.png)
Chapter 14
... phenomena are supposed to compensate some for whatever happened in the past. This is just not true. For example, when flipping a fair coin, if heads comes up on each of the first 10 flips, what do you think the chance is that tails will come up on the next flip? Thanks to the LLN, we know that r ...
... phenomena are supposed to compensate some for whatever happened in the past. This is just not true. For example, when flipping a fair coin, if heads comes up on each of the first 10 flips, what do you think the chance is that tails will come up on the next flip? Thanks to the LLN, we know that r ...
Example Toss a coin. Sample space: S = {H, T} Example: Rolling a
... Roll a red die and a green die. Find the probability of getting 10 spots in total. − Sample space,(with the first number showing the number of spots on the red die first: − S={(1,1),(1,2),...,(1,6),(2,1),...,(6,6)} − all 36 possibilities equally likely. − Which of those possibilities add up to ...
... Roll a red die and a green die. Find the probability of getting 10 spots in total. − Sample space,(with the first number showing the number of spots on the red die first: − S={(1,1),(1,2),...,(1,6),(2,1),...,(6,6)} − all 36 possibilities equally likely. − Which of those possibilities add up to ...
The Law of Large Numbers
... tails with probability 1 − p. Imagine flipping the coin over and over, with the different flips having nothing to do with each other. Define the r.v. Xi to be 1 if the ith flip is heads, and 0 otherwise. Then the sequence X1 , X2 , ... is i.i.d. 5. “Prob”. The probabilities with which (X1 + . . . Xn ...
... tails with probability 1 − p. Imagine flipping the coin over and over, with the different flips having nothing to do with each other. Define the r.v. Xi to be 1 if the ith flip is heads, and 0 otherwise. Then the sequence X1 , X2 , ... is i.i.d. 5. “Prob”. The probabilities with which (X1 + . . . Xn ...
