[pic] [pic] Markov Chain [pic] Bonus Malus Model [pic] [pic] This table justifies the matrix above: | | | |Next state | | | |State |Premium |0 Claims |1 Claim
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Orata Probability by: Jirolyn Fabro Miguel Angelo Rosales March 15, 2012 I - Introduction II - Interpretations III - Etymology IV - History V - Applications 1. Weather Forecasting 2. Batting Average 3. Winning the Lottery 4. VI - Discussion VII - I-Introduction Probability is the ratio of the number of ways an event can occur to the number of possible outcomes. Probability is expressed as a fraction or decimal from 0 to 1. Probability is
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Unit 2 – Probability and Distributions Iesha Babers American InterContinental University Abstract Many occasions can’t be predicted with absolute certainty and the best way to say how likely something will happen is to use probability. When you have a set of data that is well defined and random probabilities can be used to describe statistical numbers of outcomes divided by the number of all the outcomes. Memo To: Head of American Intellectual Union From: Iesha Babers Date:
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judgments. We also have to include appropriate probability concepts that will help limit uncertainty in certain decisions. This paper will disclose the decision to reside in the tri-state area with the probability of destructive hurricanes occurring. Next this paper will reveal concepts and the outcome from the statistical analysis that was used to determine the final decision and, the tradeoffs between accuracy and precision required by various probability concepts. As a final point, this paper will
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15 Probability space ..............................................................…......... 16 Probability properties and formulas used .........................…......... 19 Combinatorics …………………………………………………... 22 Parameters of the lottery matrices …………………………......... 25 Number Combinations .......………….………………………......... 27 Probabilities of Winning with Simple Lines .................................. 37 General formula of the winning probability ……………….
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to draw inference using uncertain data We will introduce three ways of handling uncertainty: Probabilistic reasoning. Certainty factors Dempster-Shafer Theory 1. Classical Probability The oldest and best defined technique for managing uncertainty is based on classical probability theory. Let us start to review it by introducing some terms. Sample space: Consider an experiment whose outcome is not predictable with certainty in advance. However, although the outcome of the
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Company had to go by was the average number of days that it took for the company to repair the copier if it broke down. The average was between 1 and 4 days to have the machine repaired. For this data, a probability distribution table was developed and programmed into excel. Once the probability table is loaded into excel, they are averaged into a random number range that generates numbers from 0.00 to 1.0. The system then generated an average number days it would take to repair the machine base
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Module 1 - SLP Introduction to Probability MAT201 - Basic Statistics Quantitative data gathered on the amount of time spent using the computer on a daily basis. The procedure and data was collected for ten (10) days: 1. Time logged onto the computer. 2. Time logged off the computer. 3. Total number of hours logged onto the computer per use 4. Total use time to get a daily grand total. 5. Grand total for each day. RESULTS: DAY ONE: TOTAL HOURS
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Blake Electronics Version 1: September 17th, 2014 Presented by: Case Study for Blake Electronics Company profile Blake Electronics was founded in 1979 by Steve Blake. Based in Long Beach, California, Blake Electronics manufactures various types of electronic components including resistors, capacitors, and inductors. Blake Electronics supplies components to companies that manufacture more complicated electronic equipment. Total annual sales increased $8M between 1992 and 2002 More than
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stance that risk is represented by the quantitative measure of the probability of an untoward/unpleasant event occurring. Economists tend to view risk differently. Again probability theory is used but it is applied to all possible outcomes arising out of a particular event. By multiplying the probability by the outcome an expected loss is produced. When all outcomes are multiplied by their respective probabilities a probability distribution is produced. Various means are used to measure the outcome
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