Intercultural Paper I interviewed Kotryna Klizentyte‚ who is from Lithuania. Kotryna’s family is from Lithuania‚ where she was born. Unfortunately‚ when Kotryna was young‚ her parents separated and got divorced‚ her mom went to America with $50 and made it and was able to save enough and start a new life bringing Kotryna and her sister over to America. Kotryna was about three years old when she came to America. Though she has lived in America for the majority of her life‚ she feels attached
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(Thompson‚ 2009; Berlekamp‚ 2005). Hence‚ the present discussion will first briefly overview probability in relation to random events and then present its applications to blackjack. In drawing connections between mathematics‚ more specific to our case‚ probability‚ and blackjack first requires the definition of how random events and probability relate to outcomes of random events. Probability can be defined as the way in which mathematics describes randomness. Something is considered to be random if
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is (chance‚ fairness‚ a way to observe our random world‚ the different representations) - Know what the difference between experimental and theoretical probability is - Be able to find the probability of a single event - Be able to calculate the probability of sequential events‚ with and without replacement - Understand what a fair game is and be able to determine if a game is fair - Be able to make a game fair - Be able to use different approaches (such as tree diagrams‚ area models‚
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proper notation‚ determine the following: a) b) c) d) e) Find the probability of R‚ the event that a randomly-selected person prefers a romantic movie. Find the probability of F‚ the event that a randomly-selected person is less than 40 years old. Determine the probability of R and F occurring. Are R and F mutually exclusive? (Explain using probabilities) List a pair of mutually exclusive events and explain (in probabilistic terms) why they are mutually exclusive. f) Determine the probability
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|proficiency. | |Vocabulary: |Visuals‚ Materials & Texts: | |probability‚ event‚ outcome‚ sample space‚ tree diagram |graphing calculators‚ dice‚ coins‚ poster of tree diagram‚ index | | |cards for visual/verbal
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First Problem Assignment EECS 401 Due on January 12‚ 2007 PROBLEM 1 (15 points) Fully explain your answers to the following questions. (a) If events A and B are mutually exclusive and collectively exhaustive‚ are Ac and Bc mutually exclusive? Solution Ac ∩ Bc = (A ∪ B)c = Ωc = ∅. Thus the events Ac and Bc are mutually exclusive. (b) If events A and B are mutually exclusive but not collectively exhaustive‚ are Ac and Bc collectively exhaustive? Solution Let C = (Ac ∪ Bc )c ‚ that is the
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TRIDENT UNIVERSITY INTERNATIONAL Done By: Course # MAT201 Case Module 1 Introduction of Probability Instructor: 1. In a poll‚ respondents were asked if they have traveled to Europe. 68 respondents indicated that they have traveled to Europe and 124 respondents said that they have not traveled to Europe. If one of these respondents is randomly selected‚ what is the probability of getting someone who has traveled to Europe? Outcome: selecting someone who has been
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probability theory which is often refereed to as the science on uncertainty” (Lind‚ Marchal‚ & Wathen‚ 2008). This is the number that explains the chance that something will happen. “Probability is used to mean the chance that a particular event (or set of events) will occur expressed on a linear scale from 0 (impossibility) to 1 (certainty)‚ also expressed as a percentage between 0 and 100%” (Math World‚ n.d.). There are two ways to appoint
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heart attack. If the patient survives the surgery‚ he has a 50% chance that the heart damage will heal. Find the probability that the patient survives and the heart damage heals. Let BS be the event that the patient survives bypass surgery. Let H be the event that the heart damage will heal. Then P(BS) = 0.60‚ and also we have a conditional probability: given the patient survives the probability that the heart damage will heal is 0.5‚ that is P(H|BS) = 0.5
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Probability theory Probability: A numerical measure of the chance that an event will occur. Experiment: A process that generates well defined outcomes. Sample space: The set of all experimental outcomes. Sample point: An element of the sample space. A sample point represents an experimental outcome. Tree diagram: A graphical representation that helps in visualizing a multiple step experiment. Classical method: A method of assigning probabilities that is appropriate when all the experimental
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