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- The conditional probability of E given that F occurs is P(EF)=___________. So in rolling a die the conditional probability of the event E, getting a six, given that the event F, getting an even number, has occurred is P(EF)=___________.arrow_forwardThe conditional probability of E given that F occur is P(EF)= _____________. So in rolling a die the conditional probability of the event E. “getting a six,” given that the event F, “getting an even number.” has occurred is P(EF)= ____________.arrow_forwardAssume that the probability that an airplane engine will fail during a torture test is 12and that the aircraft in question has 4 engines. Construct a sample space for the torture test. Use S for survive and F for fail.arrow_forward
- Let E and F be events in a sample space S. aThe probability of E and F occurring is P(EF)=______________. bIf the occurrence of E does not affect the probability of the occurrence F, then the events are called ____________. So in tossing a coin twice, the event E, getting heads on the first toss, and the event F, getting heads on the second toss, are ____________. cIf E and F are independent events, then the probability of E and F is P(EF)=________.arrow_forwardLet R be the set of all infinite sequences of real numbers, with the operations u+v=(u1,u2,u3,......)+(v1,v2,v3,......)=(u1+v1,u2+v2,u3+v3,.....) and cu=c(u1,u2,u3,......)=(cu1,cu2,cu3,......). Determine whether R is a vector space. If it is, verify each vector space axiom; if it is not, state all vector space axioms that fail.arrow_forward3. If {An, n ≥ 1) is an independent sequence of events, show P(An) = P(A₂). n=1 n=1arrow_forward
- The factorial function occurs often in probability and statistics. For a non-negative integer n, the factorial is denoted n! (which is read "n factorial") and is defined as follows: First, 0! is defined to be 1. Next, if n is 1 or larger then n! means n(n − 1)(n − 2)...3 ✕ 2 ✕ 1. Thus 3! = 3 ✕ 2 ✕ 1 = 6. Consult the Technology Guide to see how to enter the factorial operation on the calculator.In many counting situations, the number of possibilities is not affected by order. For example, if a group of 6 people is selected from a group of 24 to go on a trip, then the order of selection does not matter. In general, the number C of ways to select a group of k things from a group of n things is given by C = n! k!(n − k)! if k is not greater than n. (a) How many different groups of 6 people could be selected from a group of 24 to go on a trip? groups(b) How many groups of 18 could be selected from a group of 24? groups(c) Your answers in parts (a) and (b) should have been…arrow_forward3.17 Theorem Let {sn} be a sequence of real numbers. Let E and s* have the same meaning as in Definition 3. 16. Then s* has the following two properties: (a) s* e E. (b) If x> s*, there is an integer N such that n � N implies sn < x. Moreover, s* is the only number with the properties (a) and (b). Of course, an analogous result is true for s * . Proof (a) If s* = + 00, then E is not bounded above; hence {sn} is not bounded above, and there is a subsequence {snk } such that snk ) + 00. If s* is real, then E is bounded above, and at least one subsequential limit exists, so that (a) follows from Theorems 3.7 and 2.28. If s* = - 00, then E contains only one element, namely - 00, and there is no subsequential limit. Hence, for any real M, Sn > M for at most a finite number of values of n, so that Sn ) - 00. This establishes (a) in all cases. (b) Suppose there is a number x> s* such that Sn � x for infinitely many values of n. In that case, there is a number y E E such that y � x…arrow_forwardSolve itarrow_forward
- Prob q6arrow_forwardSuppose that A and B are events such that P (A|B) = P (B|A), P(AUB) = 1, and P(An B) > 0. Prove that P (A) >.arrow_forward(a) For each one of the statements below say whether the statement is true or false, explaining your answer. i. Let A and B be two events such that P(A) > 0 and P(B) > 0. If it holds that P(A|B) = 0, then P(B|A) = 1. 4 i. For two independent events A and B such that P(A) > 0) and P(B) > 0, then: P(AUB) = P(A) = P(B). iii. For a random variable X, then: Var(X)> Var(X + 2). iv. A random sample of size n is a sequence of n independent and non-identically distributed random variables. v. The standard normal distribution has fatter tails than the Student's t distribution with finite degrees of freedom. istribution witharrow_forward
- College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningAlgebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage LearningElementary Linear Algebra (MindTap Course List)AlgebraISBN:9781305658004Author:Ron LarsonPublisher:Cengage Learning
- College Algebra (MindTap Course List)AlgebraISBN:9781305652231Author:R. David Gustafson, Jeff HughesPublisher:Cengage LearningAlgebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage