probability examples on how you can define or not define a probability distribution on the set of natural numbers
7. Consider an esperinent whowe sample space coansists of allive nteger(aka matural) mumbers Z+ 1,2,3,...) (i.e....
7. Consider an experiment whose sample space consists of all positive integer (a.k.a. natural) numbers Z+ 1,2,3, ...J (i.e. choose a random natural number) a) Can you define a probability on Z+? (b) Can you define a probability on Z+ in such a way that any two numbers are equally likely to occur? (c) Along the lines of (b), can you define a probability on the interval [0, 1] in such a way that any two numbers in this interval...
7. Consider an experiment whose sample space consists of all positive integer (a.k.a. natural) numbers Z 1,2,3,...] (i.e. choose a random natural number) (a) Can you define a probability on Z+? (b) Can you define a probability on Z+ in such a way that any two numbers are equally likely to occur? (c) Along the lines of (b), can you define a probability on the interval [0, 1 in such a way that any two numbers in this interval are...
Consider an experiment whose sample space consists of all positive integer (a.k.a. nata) numbers Z, 1,2,3,..) (i.c. choose a random natural number (a) Can you define a probability on Z? (b) Can you define a probability on Z in such a way that any two numbers are equally likely to occur? leshe in d ), con you drlune a prodability on the inerv ) 0, 1] in such a w any two numbers in this interval are cqually likely to...
4. Consider the sample space S 1,2,3,...), and assume that outcomes have the probabilities P(i)- 2-'. For any n 2 0, define the discrete random variable Xn S0,... , n) by x,(i)-1 mod (n + 1), where mod means"modulo (a) Show that Xn converges in probability to the "identity" random variable X, defined by X(i)-. (b) Show that Xn converges in distribution to the Geom (1/2) random variable (e.g. to the time of the first Head in a sequence of...
CSCI-270 probability and statistics for computer Consider the sample space of outcomes of two throws of a fair die. Let Z = be the minimum of the two numbers that come up. List all the values of Z. Compute its probability distribution. Consider the sample space of outcomes of two tosses of a fair coin. On that space define the following random variables: X = the number of heads; Y = the number of tails on the first toss. For...
9. Consider the sample space Ω {1.2.3.4 } (the set of all natural numbers). We want to show that there is no probability measure on 2 under which "all outcomes are equally likely" Let's argue by contradiction. Suppose P is a probability measure such that P)) has the same value for all n e2. Let's see what can go wrong. (a) Suppose P)> 0. Which axiom of probability will be violated? (b) Suppose P((n)) = 0, which axiom of probability...
4. Consider a inap φ : I 1,11 > 10, 1] defined by φ(z) :-12. Let X and Y be random variables related by the map φ, i.c., Y-o(X) (their sample spaces are then given by SX-1 1,11 and SY-10,1]). Let FY be the σ-algebra and Hy the probability measure you worked out in problem 3. Compute the adaptod ơ algebra X and the corresponding probability measure x (i.e., use the formula X (ф ія, )-, Y (S.) for any...
5. Consider the sample space Ω = [0, 1]. Let P be a probability function such that for any interval fa, b, P(a, b-b-a. In other words, probabilty of any interval is its length Let us start with Co [0, 1, and at nth step, we define Cn by removing an interval of length 1/3 from the middle of each interval in Cn-1 For example, C1-[0, 1/3 u [2/3,1], C2-[0,1/9)U[2/9,1/3 U [2/3,7/9 U[8/9, 1] and so on. Here is a...
Consider the sample space Ω-10, 1]. Let P be a probability function such that for any interval [a, b], P([a, b) b- a. In other words, probabilty of any interval is its length. Let us start with Co 10, 1], and at nth step, we define C, by removing an interval of length 1/3° from the middle of each interval in Cn-1. For example, G = [0, 1/3ju [2/3, 11, c2 [0, 1/9] U [2/9, 1/3] U [2/3,7/9] U [8/9,...
Consider the Markov chain on state space {1,2, 3,4, 5, 6}. From 1 it goes to 2 or 3 equally likely. From 2 it goes back to 2. From 3 it goes to 1, 2, or 4 equally likely. From 4 the chain goes to 5 or 6 equally likely. From 5 it goes to 4 or 6 equally likely. From 6 it goes straight to 5. (a) What are the communicating classes? Which are recurrent and which are transient? What...