Introduction The word Probability derives from probity‚ a measure of the authority of a witness in a legal case in Europe‚ and often correlated with the witness ’s nobility. In a sense‚ this differs much from the modern meaning of probability‚ which‚ in contrast‚ is used as a measure of the weight of empirical evidence‚ and is arrived at from inductive reasoning and statistical inference. A short history of Probability Theory............ The branch of mathematics known as probability theory was inspired
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the use of statistics and the study of probability. He gives us historical background on the development of probability studies tied to games of chance; basic ideas of probability that are part of our mental arsenal and can be used in all kinds of unexpected situations; implications on statistics. First of all‚ he talks about that probabilities take their place in every part of our life‚ how can we put statistics in our life‚ how can we calculate the probability‚ which is born in the study of games
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1/08/13 Probability Primer Principles of Econometrics‚ 4th Edition Probability Primer Page 1 ! Announcement: ! Please make sure you know who your tutor is and remember their names. This will save confusion and embarrassment later. ! Kai Du (David) ! Ngoc Thien Anh Pham (Anh) ! Zara Bomi Shroff Principles of Econometrics‚ 4th Edition Probability Primer Page 2 Chapter Contents ¡ P.1 Random Variables ¡ P.2 Probability Distributions ¡ P.3 Joint
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I. Probability Theory * A branch of mathematics concerned with the analysis of random phenomena. The outcome of a random event cannot be determined before it occurs‚ but it may be any one of several possible outcomes. The actual outcome is considered to be determined by chance. * The word probability has several meanings in ordinary conversation. Two of these are particularly important for the development and applications of the mathematical theory of probability. One is the interpretation
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The Collier Encyclopedia’s definition for probability is the concern for events that are not certain and the reasonableness of one expectation over another. These expectations are usually based on some facts about past events or what is known as statistics. Collier describes statistics to be the science of the classification and manipulation of data in order to draw inferences. Inferences here can be read to mean expectations‚ leading to the conclusion that the two go hand in hand in accomplishing
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Chapter 3 Probability True/False 1. A contingency 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
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QMT200 CHAPTER 3: PROBABILITY DISTRIBUTION 3.1 RANDOM VARIABLES AND PROBABILITY DISTRIBUTION Random variables is a quantity resulting from an experiment that‚ by chance‚ can assume different values. Examples of random variables are the number of defective light bulbs produced during the week and the heights of the students is a class. Two types of random variables are discrete random variables and continuous random variable. 3.2 DISCRETE RANDOM VARIABLE A random variable is called
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The North Star Concert North Star.xls Best Guess‚ Worst Case‚ Best Case; and Continuous Uncertainties 3 Engine Services‚ Inc. Quick Start Guide to Crystal Ball Analyzing Uncertainty‚ Probability Distributions‚ and Simulation Learning Module: Crystal Ball Litigate Demo Engine Services.xls Language of Probability Distributions and Monte Carlo Simulation 4 Taurus Telecommunications Corporation: A New Prepaid Phone Card Learning Module: Tornado Sensitivity Taurus Telecommunications.xls Sensitivity
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PROBABILITY DISTRIBUTION In the world of statistics‚ we are introduced to the concept of probability. On page 146 of our text‚ it defines probability as "a value between zero and one‚ inclusive‚ describing the relative possibility (chance or likelihood) an event will occur" (Lind‚ 2012). When we think about how much this concept pops up within our daily lives‚ we might be shocked to find the results. Oftentimes‚ we do not think in these terms‚ but imagine what the probability of us getting behind
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P(S) The symbol for the probability of success P(F) The symbol for the probability of failure p The numerical probability of a success q The numerical probability of a failure P(S) = p and P(F) = 1 - p = q n The number of trials X The number of successes The probability of a success in a binomial experiment can be computed with the following formula. Binomial Probability Formula In a binomial experiment
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