– a) What is the probability of finding oil at all three of the sites? The table below shows the different events and there probabilities Event Symbol Probability The event of finding oil at 1st site A 0.70 The event of finding oil at 2nd site B 0.85 The event of finding oil at 3rd site C 0.80 Since all three events are independent and does not affect the outcome of the other so the probability of finding oil at all
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following type of random experiment: 1 The experiment consists of n repeated Bernoulli trials - each trial has only two possible outcomes labelled as success and failure; The trials are independent - the outcome of any trial has no effect on the probability of the others; 2 The Binomial Distribution Binomial Experiments Consider the following
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represent a probability distribution. *If the data represent a probability distribution‚ find its mean and standard deviation. * If the data don’t represent a probability distribution‚ identify the requirement(s) for a probability distribution that is not satisfied. The data does not represent a probability distribution because all the probabilities are between 0 and 1 but the sum of the probabilities does not equal 1. 0.22+ 0.16+ 0.21 + 0.16 = 0.75 therefore‚ this is not a probability distribution
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LOM 5300 Statistical Analysis for Business Decisions Multiple Choice Questions Chapter 1 1. In a questionnaire‚ respondents are asked to mark their gender as male or female. Gender is an example of the a. ordinal scale. b. nominal scale. c. ratio scale. d. interval scale. ANS: b 2. The scale of measurement that is used to rank order the observation for a variable is called the a. ratio scale. b. ordinal scale. c. nominal scale. d. interval scale. ANS: b 3. Some hotels ask their guests to
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Economics 520 Lecture Note 9: Introduction to Stochastic Processes This Version: October 5‚ 2013 These notes are based on S. Ross‚ Introduction to Probability Models‚ Academic Press‚ and J. Hamilton‚ Time Series Analysis‚ Princeton University Press. Definition 1 A stochastic process {X (t )‚ t ∈ T } is a collection of random variables: for each t ∈ T ‚ X (t ) is a random variable. The set T is called an index set‚ and t ∈ T is often interpreted as time. So X (t ) would be the (random) state
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report‚ will we go through and determine which judges in the county are making too many mistakes. 1. The probability of a case in Hamilton County being appealed and reversed in Common Pleas Court .04462 Domestic Relations Court .00403292 Municipal Court .005556867 2. The probability of a case being appealed for each judge Common Pleas Court Judge Probability of case appealed * Fred Cartolano .04511 * Thomas Crush .03529 * Patrick
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Markovian targets which is detailed in El-Hadidy (Asia-Pac. J. Oper. Res. 33(3):1650019 (30 pages)‚ 2016). At each fixed number of time intervals‚ the search effort is a random variable with a normal distribution. More than minimizing the undetection probability of the targets at time interval i‚ we seek for the optimal distribution of the search effort by maximizing the discounted effort reward search. We present some special cases of one Markovian and hidden target. An experimental results for a Markovian
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Gain Combiner ) Diversity system is consider. The ucorrelated Rayleigh fading is presented. The cumulative density function - CDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined. The probability density function -PDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined. Keywords – EGC‚ PDF‚ CDF‚ Fading‚ Rayleigh‚ Combiner. I. Introduction PROBLEMS THAT OCCUR DURING
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preferences. It does not require reference to objective probabilities‚ personalistic consequences‚ or counterfactual acts‚ and it allows for state-dependence of utility and unobservable background risk. The decision maker’s local beliefs are encoded in her risk neutral probabilities (her relative marginal rates of substitution between states) and her local risk preferences are encoded in the matrix of derivatives of the risk neutral probabilities. This matrix plays a central but generally unappreciated
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.2 R v Sally Clark (1999) 5.2.a Danger of multiplying probabilities together One of the laws of probabilities states that when the events are independent of each other their probabilities can be multiplied together. This is called the product rule. In the trial‚ Roy Meadow was asked to present some statistical information as to the happening of two cot deaths within the same family. It was explained to the jury that there were factors that were suggested as relevant to the chances of a Sudden Infant
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