"Catastrophic events" Essays and Research Papers

of the basic rules of probability: the sum of the probability that an event will happen and the probability that the event won’t happen is always 1. (In other words‚ the chance that anything might or might not happen is always 100%). If we can work out the probability that no two people will have the same birthday‚ we can use this rule to find the probability that two people will share a birthday: P(event happens) + P(event doesn’t happen) = 1 P(two people share birthday) + P(no two people share

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13 4. Introduction to Probability ....................................................................... 15 5. Unions‚ Intersections‚ and Complements ................................................ 23 6. Conditional Probability & Independent Events..................................... 28 7. Discrete Random Variables....................................................................... 33 8. Binomial Random Variable ...................................................................... 37

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weights. Then 6 1 ‚...‚m(ω6 ) = 21 . (Check for yourself that this choice of values of m(ωi ) satisfies m(ω1 ) = 21 the three conditions above!) Therefore‚ P (Even) = P ({2‚ 4‚ 6} = 2 21 + 4 21 + 6 21 = 12 21 = 4 7 = 0.57. 7. Let A and B be events such that P (A ∩ B) = 14 ‚ P (Ac ) = 13 ‚ and P (B = 12 . What is P (A ∪ B)? Recall Theorem 4 from class: P (A ∪ B) = P (A) + P (B) − P (A ∩ B). We already know that P (B) = 12 and P (A ∩ B) = 14 ‚ so we just need to find P (A). By Theorem 1 part

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shift requires 6 operators‚ 2 maintenance persons‚ and 1 supervisor‚ in how many different ways can it be staffed? [8 points] 18 10  4       18564  45  4  3‚341‚520  6  2  1  (b) Suppose A and B are not mutually exclusive events‚ and we have P(A)=0.35‚ P(B)=0.40‚ P(AB)=0.18. Compute the following probabilities: i) P (AB)=? [4 points] P (AB)=P[A]+P[B]-P[AB]=0.35+0.40-0.18=0.57 ii) P(AB)=? P[A  B]  P[ A  B] 0.18   0.45 P[ B] 0.40 1 of 6 [4 points] Name: Problem

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input the probabilities of 0.4‚ 0.4 and 0.2 for “good”‚ “moderate” and “poor” market reception. We then proceed to develop the marginal‚ conditional‚ and joint probabilities for each terminal end-point. The formula for the conditional probability of events A and B is changed as: P(A ∩ B) = P(B) P(A | B) By developing the likely revenue of market response outcome and summing the results‚ we obtain the expected

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PROBABILITY QUESTIONS Q1). You draw a card at random from a standard deck of 52 cards. Neither you nor anyone else looked at the card you picked. You keep it face down. Your friend then picks a card at random from a remaining 51 cards. a) What is the probability that your card is ace of spades? 1/52 b) What is the probability that your friend’s card is ace of spades? (Hint: Construct the sample space for what your friend’s card can be.) 1/51 c) You turn over your card and it is 10 of

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specific event will occur. If the event is A‚ then the probability that A will occur is denoted P(A). Example: Flip a coin. What is the probability of heads? This is denoted P(heads). Properties of Probability 1. The probability of an event E always lies in the range of 0 to 1; i.e.‚ 0 ≤ P( E ) ≤ 1. Impossible event—an event that absolutely cannot occur; probability is zero. Example: Suppose you roll a normal die. What is the probability that you will get a seven? P(7) = 0. Sure event—an event that is

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UNIT CODE: BIT 3102 UNIT TITLE: EVENT DRIVEN PROGRAMMING Assignment Two This assignment focuses on the following • Controlling program flow using if control structure and select case control structure • Use of option buttons and checkboxes Create a VB project and save it as assignment two – your name and in this project add the following forms i. A form that reads in a student’s cat1‚ cat2 and final exam marks then computes the total and displays the total in a text box. It then displays

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table is a tabular summary of probabilities concerning two sets of complementary events. Answer: True Difficulty: Medium 2. An event is a collection of sample space outcomes. Answer: True Difficulty: Easy 3. Two events are independent if the probability of one event is influenced by whether or not the other event occurs. Answer: False Difficulty: Medium 4. Mutually exclusive events have a nonempty intersection. Answer: False Difficulty: Medium (REF)

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Objectives of Current Lecture In the current lecture:  Introduction to Probability  Definition and Basic concepts of probability  Some basic questions related to probability  Laws of probability  Conditional probability  Independent and Dependent Events  Related Examples 2 Probability  Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement is true. For example‚ it is very likely to rain today or I have a fair chance of passing

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