Case study Simulation of data To illustrate usage of Zebu‚ data simulated using a bayesian network will be used. The example presented in figure 1 is borrowed from Pearl [25]. Five thousand cases with 5% of missing data was simulated using SamIan. To illustrate how Zebu handles continuous variables‚ calcium concentrations were simulated. ”Not increased” cases were randomly sampled from a normal distribution with mean 2.4 and standard deviation 0.05. ”Increased” cases were randomly sampled from an
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doing a good job and which ones were making too many mistakes. You are to assist in the data analysis by using your knowledge of probability and conditional probability to help with the ranking of each of the judges‚ as well as each court. Managerial Report Prepare a report (see below) with your ranking of the judges based on the probabilities and conditional probabilities‚ as well as the analysis of each court. Include the following seven (7) items in table format to support your ranking. Be sure to
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STAT 233 Midterm Review Questions 1. A local hotdog vendor that works the entire downtown area has determined the following payoffs for 3 possible strategies. Strategy A is to locate at one central location. Strategy B is to push the cart around to cover the entire downtown area. Strategy C is to locate inside one of the small shopping centres. Strategy Rainy Overcast Sunny A B C $500 -150 920 700 500 400 900 1200 100 What is the decision and value of the decision using: a. b. c. Optimistic
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Group Sampling plan as reference plan. Further they studied the QSS-1‚ QSS- 2 and QSS-3 with Conditional Repetitive Group Sampling (CRGS)‚ Multiple Repetitive Group Sampling (MRGS) and Two-Stage Repetitive Group Sampling (TSRGS) plan as reference plan. Kaviyarasu et al (2014) has Proposed Designing of repetitive Group Reliability Sampling Scheme (RGRSS) Through Basic Quality Levels. It follows the acceptance sampling methodologies in life time of the product through exponential distribution and parameters
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Statement of the problem: a. Should Steve contract the services of an outside research agency? b. If survey is warranted‚ should he employ MAI or I&K? c. Should the new product line be introduced? MAI’s proposal directly gives Steve the conditional probabilities he needs (e.g.‚ probability of a successful venture given a favorable survey). Although the information from Iverstine and Kinard (I&K) is different‚ we can easily use Bayes’ theorem to on I&K information to compute the revised probabilities
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The movie 21 There is one thing I like in this movie‚ Trick math and card counting was one of the fascinating thing in the movie and the introduction of the principle of variable change (The Monty hall problem and conditional probability). A game show host tells a contestant to choose between three doors. Two doors have a goat behind them…and the other has a brand new car. He tells the contestant to choose a door. The contestant chooses door #1. Then‚ the host‚ knowing what is behind each door
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are often the result of mistakes made by judges‚ and the newspaper wanted to know which judges were doing a good job and which were making too many mistakes. You are called in to assis in the data analysis. Use your knowledge of probability and conditional probability to help with the ranking of the judges. You also may be able to analyze the likelihood of appeal and reversal for cases handled by different courts. Managerial Report Prepare a report with your rankings of the judges. Also‚ include an
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often the result of mistakes made by judges‚ and the newspaper wanted to know which judges were doing a good job and which were making too many mistakes. You are called in to assist in the data analysis. Use your knowledge of probability and conditional probability to help with the ranking of the judges. You also may be able to analyze the likelihood of appeal and reversal for cases handled by different courts. Managerial Report Prepare a report with your rankings of the judges. Also‚ include
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(A ∩ Bc ) ∪ (Ac ∩ B) = (A ∪ B) ∩ (A ∩ B)c Thus‚ P (A ∪ B) ∩ (A ∩ B)c = P(A ∪ B) + P (A ∩ B)c ) − P (A ∪ B) ∪ (A ∩ B)c = P(A ∪ B) + 1 − P(A ∩ B) − P(S) = P(A ∪ B) − P(A ∩ B) = 0.2 This is the same expression as in (1). (b) Determine the conditional probability that he is a thief‚ given
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Chapter 4 Introduction to Probability Case Problem: Hamilton County Judges The data in the table provides the basis for the analysis. We provide notes as a guide to answering questions 1 through 5. 1. The conditional probabilities of cases being appealed in the three courts are given in the 3 Total rows in the table. For Common Pleas Court‚ the probability of an appeal is .0401; for Domestic Relations Court‚ the probability of an appeal is .00348; and for Municipal Court‚ the
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