Concept explainers
In Problems 3 to 12, find the average value of the function on the given interval. Use equation ( 4.8 ) if it applies. If an average value is zero, you may be able to decide this from a quick sketch which shows you that the areas above and below the
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Mathematical Methods in the Physical Sciences
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- 5. State without proof the uniqueness theorem of a probability function (arrow_forward2. (a) Define lim sup A,. Explain when an individual element of 2 lies in A* = lim sup A. Answer the same for A, = lim inf A,,.arrow_forward(c) Show that the intersection of any number of a-fields is a g-field. Redefine (A) using this fact.arrow_forward
- (b) For a given sequence A, of subsets of 92, explain when we say that A,, has a limit.arrow_forward1. Let 2 (a, b, c} be the sample space. (b) Construct a a-field containing A = {a, b} and B = {b, c}.arrow_forward2= 1. Let 2 {a, b, c} be the sample space. (a) Write down the power set of 2.arrow_forward
- Theorem: show that XCH) = M(E) M" (6) E + t Mcfic S a Solution of ODE -9CA)- x = ACE) x + g (t) + X (E) - Earrow_forwardExercise 1 Given are the following planes: plane 1: 3x4y+z = 1 0 plane 2: (s, t) = ( 2 ) + ( -2 5 s+ 0 ( 3 t 2 -2 a) Find for both planes the Hessian normal form and for plane 1 in addition the parameter form. b) Use the cross product of the two normal vectors to show that the planes intersect in a line. c) Calculate the intersection line. d) Calculate the intersection angle of the planes. Make a sketch to indicate which angle you are calculating.arrow_forward1. Let 2 (a, b, c)} be the sample space. (a) Write down the power set of 2. (b) Construct a σ-field containing A = {a, b} and B = {b, c}. (c) Show that F= {0, 2, {a, b}, {b, c}, {b}} is not a σ-field. Add some elements to make it a σ-field..arrow_forward
- 13. Let (, F, P) be a probability space and X a function from 2 to R. Explain when X is a random variable.arrow_forward24. A factory produces items from two machines: Machine A and Machine B. Machine A produces 60% of the total items, while Machine B produces 40%. The probability that an item produced by Machine A is defective is P(DIA)=0.03. The probability that an item produced by Machine B is defective is P(D|B)=0.05. (a) What is the probability that a randomly selected product be defective, P(D)? (b) If a randomly selected item from the production line is defective, calculate the probability that it was produced by Machine A, P(A|D).arrow_forward(b) In various places in this module, data on the silver content of coins minted in the reign of the twelfth-century Byzantine king Manuel I Comnenus have been considered. The full dataset is in the Minitab file coins.mwx. The dataset includes, among others, the values of the silver content of nine coins from the first coinage (variable Coin1) and seven from the fourth coinage (variable Coin4) which was produced a number of years later. (For the purposes of this question, you can ignore the variables Coin2 and Coin3.) In particular, in Activity 8 and Exercise 2 of Computer Book B, it was argued that the silver contents in both the first and the fourth coinages can be assumed to be normally distributed. The question of interest is whether there were differences in the silver content of coins minted early and late in Manuel’s reign. You are about to investigate this question using a two-sample t-interval. (i) Using Minitab, find either the sample standard deviations of the two variables…arrow_forward
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