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208
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Bayesian Estimation

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...Bayesian and Traditional Estimation Techniques in Statistics Introduction The statistics is an art and science of estimating the unknown. The unknown parametric values about the population of a particular sort are determined with the help of sample’s figures and values. The estimation techniques developed in their sophistication with the passage of time. However, the modern one is known as Bayesian estimation. The statistics is a science of inexactitude and therefore, the Bayesian approach considers everything as a possibility and assigns a certain figure to its probability of occurring (Aldrin, Holden and Guttorp, 256). Probability is a number between 0 and 1... Paper An Analytical Comparison of...

Bayesian Networks

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...Bayesian networks (BNs) have established fairly well as useful symbols of knowledge for reasoning under uncertainty quite recently.However, the modelling ideas they are based on have been around for some time. The statistician Wright [16] first introduced the representation in 1921 for the analysis of crop failure. Many researches [4, 5, 9, 14, 15] recreated it in different names, such as causal network, causal probabilistic network, graphical probability networks, belief network, and influence diagram. Bayesian networks, are also called, generative models, probabilistic cause-effect models or causal models.
BNs are graphical models that set probabilistic relationships among variables... 1 Introduction...

Scaling-up Bayesian Networks:

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...Bayesian Networks - Submission
Name of Professor
Number of Words: 787
Table of Contents
I. Title ……………………………………………………………. 3
II. Introduction …………………………………………………… 3
III. Purpose ………………………………..……………………… 3
IV. Problem Statement ………………………………………….. 4
V. Significance of the Problem ………………………………… 4
VI. Research Question …………………….…………………….. 4
VII. Research Design …………………………………………….. 5
VIII. Data Collection Method / Instrument(s) ………..………….. 5
IX. Data Analysis ……………………………….………………... 6
X. Cost / Feasibility Analysis …………………………………… 6
XI. Conclusion …………………………….………………….…… 6
References... ……………………………………………….…………… 7
Title:
“Narrowing the Complexity of Scaling-Up the Bayesian...

Computational MCMC Bayesian Inference

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...Bayesian Inference Computational MCMC Bayesian Inference The Markov Chain Monte Carlo (MCMC) method employs Markov Chain to simulate Monte Carlo experiments. These experiments provide estimates to quantities by executing statistical experiments. MCMC takes a Bayesian approach to conduct the essential mathematical integration using simulation. In the Bayesian inference framework, probability estimation is used to quantify the uncertainty in the parameters (Chen, 2010). The data is certain and is considered fixed. On the other hand, parameters are uncertain and thus are represented as random variables. Since it is not usual to consider a single value of a parameter, we get... a posterior...

Estimation of UAE population using Bayesian Theorem

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...Bayesian theory The Bayes theory was brought forward by Thomas Bayes in the 1700s who also worked towards creating the probability distribution bounds of binomial distributions. However, his work was brought forward by a friend of his, Richard Price, after his death (Bayes’ theorem, trinity.edu). Bayesian theory has been used in the development of several other models in which the participants may be concerned with determination of other growth concepts. A common use to which this theory has been put to is the development of time series forecasts for populations. In this case, this theory will be used to analyze the population data for United Arab... Estimation of the population of UAE using the...

Bayesian analysis of HMM-GARCH models in Finance

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...Bayesian analysis of HMM-GARCH models in Finance Table of Contents Table of Contents 2 Abstract 3 Introduction to the Problem 4 Purpose of the Study 4 Research Objectives 5 Research Question 6 Literature Review 7 Research Methodology 10 Reflection on Limitations 10 Ethical Concerns in the Research 11 Conclusion 12 Abstract This research paper aims to explain methodologies for the Bayesian assessment of solitary- regime, as well as a system- switching Generalized Autoregressive Conditional Heteroskedasticity models. These two models under analysis are important equipments in financial analysis. Financial modelling professionals prefer using the GARCH...

Two behavioural finance problem sets related to Temporal Discounting and Bayesian Learning vs Reinforcement Learning in Financial Decision making

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...Bayesian learner, Mr. Spout decision will be influenced by uncertainty knowledge and the time is linked through the process of learning of the stocks.
Question... Behavioural Finance by Optional Problem Set Question For this set, to calculate the present value of CHF, you maximise utility subject to the first period, second period, and third period consumption. Utility is computed by substituting the discounting factor into the equation as shown in (i), the hyperbolic discounting is left as a symbol for the time for purposes of calculation. From the maximization equation ii, find the First order condition of consumption period 1 as shown below. As shown in iii, after computing the unknown values with...

Bayes' Theorem

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...Bayesian Theorem Introduction Reverend Thomas Bayes developed Bayes’ theorem of probability. The theorem provides understanding about the how the probability of a theorem is affected by a new set of evidence. It is applied to in a variety of context to explore a relationship between theory and evidence. Contemporary, the theorem’s application is broad, ranging from mathematics to the field of science. It explains the relations between two theories and evidences. It allows the researcher to determine the relation between current beliefs with respect to previous beliefs and evidences.
Simon Jackman (2009) defines Bayes’ theorem as ‘a theorem that illustrates conditional probability of the set... ...

Modelling Operational Risk by AMA

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...Bayesian interference comes in as an important form of Loss Distribution Approach (LDA) used from a statistical perspective in quantifying the frequency and severity distributions for bank operational risks (Akaike, 1983). On the whole, the Bayesian inference works by quantifying distributions for both frequency and severity of operational losses... by the use of statistical procedures (Neil, Häger and Andersen, 2009). Lavin and Scherrish (1999) stressed that these statistical procedures are always expressed as random vector of data based on risk cells that have specified density for a given vector of parameter.
Shevchenko (2011) associated that Bayesian inference to a number...

Research: Machine Learning

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...Bayesian network is used to convert the existing non-spatial and non-temporal disease outbreak revealing systems. This will lead to early detection of disease, accuracy and also reliability. Early disease outbreaks detection will lead to improved... Research: Machine Learning Spatio-temporal method for disease outbreak detection A disease outbreak surveillance system monitors occurrence of disease outbreaks in a region. A spatio surveillance is a special kind of a system that searches the region’s (being monitored) spatial sub-regions for patterns of disease outbreaks. By analyzing pattern change in a given period of time, a temporal surveillance system looks for new patterns of outbreak disease. A...

Summarize statistical paper

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...Bayesian Updating of Toxic Leakage Scenario Summary: In this article by Lerche (2001) has illustrated application of Bayesian Probability in a scenario of great importance of humanity. As we all know, energy is something very – very essential for survival of life in general and of mankind in particular on this planet. In the quest of energy, mankind came to know of nuclear energy; a very concentrated form of energy. Nuclear energy is realized by converting mass into energy according to the famous mass-energy equivalence relation given by Albert Einstein in his Special Theory of Relativity. The equation is E = mc2. To convert mass into energy one needs to...

Probability Theory in Decision Making

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...Bayesian logic for making any analysis only from data collected from other countries where it has its operations currently. This is because CoffeeTime is new to India and as such gathering any past historical data from the cities around mumbai is not possible. Generally any Bayesian analysis uses past experience, guesses or convenient assumptions in the form of a prior distribution. Under the present situation, the company is basically interested in calculating the profits involved in selling a particular brand of coffee in Mumbai.
The usefulness of applying the Bayesian logic using the data collected... Recently, the company is considering selling fruit juices along with coffee at the ongoing ...

Data Mining - Questions to answer

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...Bayesian learning
Combining networks
2. Why is Data Cleansing a complex, time-consuming and an error-prone process Explain
Data cleansing is the process of removing inaccurate and inappropriate data records, which is an integral process of data processing and maintenance. In large data sets, the process of finding error and correcting the same needs interaction with the domain experts which is an expensive and time consuming process. Since it involves a comprehensive assignment... 1. Is a Neural Network with one or more hidden layers more powerful than a single layer perceptron Explain (Hint: in terms of learning can a neuralnetwork with one or more hidden layers learn functions more complex than the...

Data Mining Theory

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...Bayesian classification (Naive Bayes), Support Vectors Machines (SVM) and Lazy Learners (k-NN). 1- Introduction The one of the most useful techniques of data mining is classification that is a machine learning method employed to forecast cluster association for data samples. For instance, we can desire to utilize classification to forecast whether the weather of a specific week’s day will be “damp”, “bright” or “overcast”. Well-known classification methods comprise decision trees as well as neural networks (Chapple). Additionally, the technique... ?Data Mining Theory Institute Data mining is a process of extracting concealed analytical information from huge databases. Additionally, it is a great...

Data Mining Theory

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...Bayesian classification (Naive Bayes), Support Vectors Machines (SVM) and Lazy Learners (k-NN).
1- Introduction
The one of the most useful techniques of data mining is classification that is a machine learning method employed to forecast cluster association for data samples. For instance, we can desire to utilize classification to forecast whether the weather of a specific week’s day will be “damp”, “bright” or “overcast”. Well-known classification methods comprise decision trees as well as neural networks (Chapple).
Additionally... Data Mining Theory Institute Data mining is a process of extracting concealed analytical information from huge databases. Additionally, it is a great innovative...

Nate Silvers The Signal and the Noise

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...Bayesian techniques of statistics analysis, should be at all times be re-examined and constantly reviewed. They should be established on a total agreement among those predicting data. The fundamental idea in his book is that forecasting is an important fragment of scientific and political analyses, financial markets and businesses, and virtually everything around us. Predictions are totally inevitable. Nate Silver offers practical experiences in the real life situations a serious focus on what actually transpires in research. In order to search for truth in what exactly happens in data analysis, he goes an extra... ? NATE SILVER’S ‘THE SIGNAL AND THE NOISE’ Nate Silver’s ‘The Signal and the Noise’ Nate...

Book Review on book titled, The Signal and the Noise: Why Most Predictions Fail-But Some Don't by Nate Silver

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...Bayesian techniques of statistics analysis, should be at all times be re-examined and constantly reviewed. They should be established on a total agreement among those predicting data.
The fundamental idea in his book is that forecasting is an important fragment of scientific and political analyses, financial markets and businesses, and virtually everything around us. Predictions are totally inevitable. Nate Silver offers practical experiences in the real life situations a serious focus on what actually transpires in research. In order to search for truth in what exactly happens in data analysis, he goes an extra mile... NATE SILVER’S ‘THE SIGNAL AND THE NOISE’ Nate Silver’s ‘The Signal and the Noise’...

Statistical data in a business context that requires a decision. Use probability concepts to formulate a decision

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...Bayesian decision theory (calculation of expected profits) the restaurant chain has succeeded in reducing the uncertainty of decision making.
Statistical decision theory or Bayesian decision theory finds much application in business decision making. Managers of small and large businesses find it very useful. It is named after Reverend Thomas Bayes. Reverend Bayes was trying to prove the existence of God through the application of probability when he came upon his decision theory (Richard I. Levin, David S. Rubin 271).
References:
Richard I. Levin, David S. Rubin. Statistics for Management. New York: Pearson, 2010.
Berenson M.L., Levine D.M. Basic business...

Why Is Decision-Making More Normative

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...Bayesian inference, also referred to as Bayes’ theorem, is applied to help in comprehending the level an idea can be influenced by evidence. According to Bayesians understanding, probability is arrived at due to some personal level of confidence. An individual can convey confidence that an identified event will occur, and this in turn, is seen as the probability of the identified event occurring. On the other hand, frequentists... . In accordance with heuristics and biases literature, people do not comprehend concerning probabilities in a normative way. Contrary to the above expression, it is essential to note that evolutionary psychologists argue that people’s reasoning goes hand in hand with...

: RISK ASSESSMENTS OF SHIP COLLISIONS IN HIGH-TRAFFIC MARINE TERRITORY

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...Bayesian Network (BN) was employed as an assessment tool to model and quantify the potential failure events that could lead to ship collision. In this paper, the encounter types were introduced as an additional major risk that leads to ship collisions. By implementing BN in risk assessments, one could identify a set of major critical components... PROJECT- II REPORT IME864: Risk Analysis Fall, Wichita Wichita, KS USA PROJECT-II: RISK ASSESSMENTS OF SHIP COLLISIONS IN HIGH-TRAFFIC
MARINE TERRITORY
Abhishek Pratap Singh
Wichita State University
Wichita, KS, USA
Email: apsingh@wichita.edu
Amirmahyar Abdolsamadi
Wichita State University
Wichita, KS, USA
Email: axabdolsamadi@wichita.edu
Mohammed Alharbi
Wich...

Scientific Writing

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...Bayesian and introspective. They advocated the need for Rooter development to locate mobile communication. These researchers claim a similarity between their works with the information contained in the Bayesian publication. They argued that they were the first people to come up with the idea of Lamport clocks. Their work could not be published due to red tape. Other related experiments include the construction of encrypted... Rooter: A Methodology for the Typical Unification of Access Points and Redundancy My paper entails an analysis of Rooter:A Methodology for the Typical Unification of access Points and Redundancy as a fake research paper published in 2005. . The authors of this study are Jeremy...

Discussion #3 STAT

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...Bayesian analysis. “Introduction to Probability and Statistics” is one such course offered by this website that is most closely related to what we have studied in the course as it gives an insight into the basics of probability and statistics. Topics in this course include basic models of probability, confidence intervals and linear regression. The best feature of this website is that the course content is supported with exams as well as their solutions. In this sense, this website is a complete online source of education.
Works Cited:
“Unlocking Knowledge, Empowering Minds.” 2012. Web. 11 Mar. 2012.
.... 11 March Online Learning Resources for Statistics “MIT Open Ware is a free publication of MIT...

Data summry

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...Bayesian information criteria (BIC). As the results indicated, the two-parameter is less than three-parameter approach.... Summary From the analysis of the data, the outcome revealed that everybody indicated the positive response (yes) in EVO_dev_million question. As such, the screen result indicated 1 1, as noted.
With regard to the Cronbachs alpha for all items, the findings indicated that the result is good; meaning that the internal consistency between the items are high or the agreement of the response between the items is good.
Likewise, on the screen, findings revealed the Cronbach alpha correlation coefficient, excluding Complex_chance equal 0.8065. This simply means that Cronbach alpha was ...

Knowledge

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...Bayesian and inductive inferences
Understanding the concept of automatic logical inference and the incorrect inference
Understanding the Bayesian statistics and probability logic
5.
Understanding Hume’s arguments on miracles
Analysis of Bayes theorem and application of theorem to miracles
Hume’s argument and price... Paper Knowledge The below bullet points are some of the areas to be studied to answer the questions listed under knowledge and self assessments
1.
John Locke’s Theory of Knowledge and human understanding
John Locke’s philosophy on mind and thought; an analysis on how human beings think and express themselves through logic, language and religious practices.
Reading of the book ...

Compare and contrast gigerenzers approach to judgment with that of kahneman and tversky

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...Bayesian inference problems. It has become an established fact that people give a lot of concentration to base problems of the same type. This was known as conservatism, which was a misconception. Kahneman and Tversky disagreed... with this in the 1970s and 1980s, claiming that people do not really concentrate on such problems or rather people give very less concentration to such problems. Kahneman and Tversky used the same explanations and facts in their argument. They used the process of error inside the mind. Later, the intuitive Bayesian reasoning took a new root or line of reasoning, especially of the angle of ecological. On the other hand, Gigerenzer argued that an...

Test item reliability-ANOVA

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...Bayesian approach to regression, ANOVA, mixed models and related analyses. Amsterdam: Elsevier.
Girden, E. R. (1992). ANOVA: Repeated measures. Newbury Park, Calif: Sage Publications.... College Assignment HISTORICAL EVENT SPECIFIC TESTING SCENARIO During a soccer match, one footballer aims the ball to thegoal, the keeper is far away from the game and he has high chances of scoring. However one of his teammates touches the ball as it passes him and the result is a score. A closer look at the facial expression of the first player indicates that even though they scored, he is not happy for his teammate as he expected to make this score. This should not always be the case and the player obviously denies...

Population genetics

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...Bayesian theorem developed by Professor Donnelly of Oxford University. This formula entails the multiplication of values assigned to various probabilities... such as the probability that the crime was committed by another man, the possibility of the suspect not being identified in a line-up by the victim and the probability of the alibi. The judge agreed and directed the jury to use the formula, but Adams was nevertheless, found guilty [18].
At the appeal court, the Bayesian approach was assailed by the Court as having trespassed into an area specifically reserved for the jury to determine. The Court held that it was the jury’s duty and function to consider all evidence...

Paraphase 5 abstracts

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...Bayesian inferences and Bayesian Networks, simulates a machine learning task and applies probability concept in analysis. The author also offers a model that is based on Bayesian Network to determine level of trustworthiness of Quality of services in the internet. With test of validity, the researchers establish that statistical distributions for determining levels of trust of web services are flexible, precise, and are significant... ?Paraphrase of s Freight train optimization and simulation by Thai Hoa Le The schedule that trains follow has captured significant interest among different stakeholders and this applies to both freight and passenger trains. There has been a growing demand for the rail...

Population genetics

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...Bayesian theorem developed by Professor Donnelly of Oxford University. This formula entails the multiplication of values assigned to various probabilities such as the probability... ?DNA as Evidence: Skirting the Fallacies 0 Introduction The use of DNA, which is short for deoxyribonucleic acid, in identifying a person’s geneticmake-up and distinguishing it from others is a major breakthrough in criminal investigations. This began when Dr Alec Jeffreys, an English geneticist, isolated a region in the DNA strand that contains a consistently replicated DNA sequence, which is unique to an individual. This further led him to formulate DNA typing or the process of isolating that region of the DNA strand and...

Personal experience

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...Bayesian Updating may be used. Bayesian Updating is a process is a statistical process of using new process to update probability estimates (Bern70). Reappraisal can be commonly applied to view ambiguity as a very big opportunity to get and attain knowledge. If ambiguity is used over several times and repeatedly then it can be quickly changed into a risk.
In the community, there has... Personal experience The amygdale is a twitchy character which has a very long memory in encoding an unpleasant association. When the unpleasant association has been encoded in the amygdale, it does not forget. Reappraisal can be used for short term stressors such as the fear of public speaking. Public speaking fear may be ...

Score Normalisation in Voice Biometrics (CASE STUDY)

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...Bayesian method and standardization of score distributions are two score normalisation methods. Bayesian methods include cohort normalization, world model normalisation, and unconstrained cohort normalisation. Standardisations of score... Method: The method is given by the expression, where n is the normalized score, s is the raw matching score, mean(S) is the arithmetic mean and std (S) is the standard deviation.
Tanh Method: The method is given by the expression , where n is the normalized score, s is the raw matching score, mean(S) is the arithmetic mean, std(S) is the standard deviation, and tanh() is a trigonometric operator.
Score Normalisation...

Analyzing and contrasting data mining based network intrusion detection system

46 pages
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...Bayesian Model Diagram Panda & Patra (2007)…………………………………….25 Chapter 1 Introduction In this age... ?Analyzing and Contrasting Data Mining-Based Network Intrusion Detection Systems In this present era the computers are sophistically connected to each other in a form of network. In such networks there is every possibility of intrusion to important data. In order to maintain the integrity, network data has to be secured. Electronic commerce (e-commerce) has made Internet usage most important part in everyone’s life and has become a major source of sending and receiving information. However, providing protection to the computers connected in a network is still a main issue to be tackled. In general, every...

Suicide and Pesticide Use among Pesticide Applicators and Their Spouses in the Agricultural Health Study

2 pages
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...Bayesian and the Akaike information criterions." Under the stratifying models the researchers compares the HRs using the two strata, these models included the race and the marital status. The marital status and the race categories include the individuals that had ever used pesticides and those diagnosed with diabetes.
The authors results collected showed that the risk for suicide was high for the participants more than 65 years of age, the divorced participants, those living in North Carolina, those participants that smoked, those participants that drunk alcohol. Many of the participants with the risk of committing... ENVIRONMENTAL STUDIES The articles focus on suicides among farmers and the relation...

Angioplasty

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...Bayesian methods for evidence synthesis in cost-effectiveness analysis. Pharmacoeconomics;24:1–19.
Asseburg... Angioplasty Introduction With the rising burden of atherosclerotic vascular diseases specially cardiovascular diseases worldwide and given the established morbidity and mortality associated with this disease, since its introduction angioplasty did experience an astronomical growth. Throughout the world, angioplasty remains the most frequently performed procedure performed in the hospitals as well as in the discipline of interventional cardiology. This growth had been attributable to better equipment, technological advancement, and better design of the catheters. Better understanding of the...

Combining Anomaly and Signature based Intrusion Detection Systems to offer superior detection

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...bayesian algorithm A vast amount of research is in progress related to Incident detection as various intelligence-learning algorithms are deployed for the construction of massive complex and dynamic datasets in order to improve IDS. However, researches and various studies have improved the process of Intrusion detection, still some challenges needs to be addresses, such as classifying huge datasets of intrusion detection, accuracy... ?Combining Anomaly and Signature based Intrusion Detection Systems — The study demonstrates the functionality of Anomaly and Signature basedIDS along with its advantages and disadvantages where applicable. The later parts of the body illustrate studies and researches related ...

Statical Data in a Business

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...Bayesian Analysis of the Linear Model Subject to Linear Inequality Constraints. Journal of the American Statistical Association, 73, 573-579.
Peebles, P. Z. (1993). Probability, Random Variables, and Random Signal Principles, 3rd ed. New York: McGraw-Hill, Inc.... Introduction This paper will involve use of Bayes’ theorem to establish the cost of defective products that are produced by the two plants of a detergent producing company, one located in Florida and the other one in Texas. Bayes theorem, therefore, will be used to make decision in scenarios whereby the outcome of different events is not known with certainty (Davis, 1978).
Data methods and analysis
A detergent manufacturing company has two ...

Ethics, Privacy, and Security - Case Study -- [S5]

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...Bayesian Content Filtering and the Art of Statistical Language Classification. No Starch Press,.... How do the interests of computer users differ from the interests of spammers? Spammers work under a specific agenda and policy and thereby have a different course of action to their online activities. The ordinary user uses it in a more logical and natural manner and the others use it in an abrupt manner, while ordinary users use it for purposes pertaining to the private usage and other resources. Common user might be a student, a technology follower, a news follower, gardening follower, sports follower and all the uses of such computer users are for peaceful purposes. Spammers use them to access different ...

Business Intelligence Analysis

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...Bayesian network
They are graphical models that are used to simplify the computations involved in car sales. Their advantage is that they exhibit a high accuracy.
Simulations
The data... and prediction rate. Evidently, the Bayesian classifier had the highest accuracy that is, 98.6111% with a time of 0.17 secondswhile the Decision tree had the least that is, 81.9444% with 0.62 seconds. Deducing from this data, the Bayesian is clearly the best strategy among the three because of its hiogh accuracy and its fast capability. The car data set has 1729 instances and 7 attributes.
=== Run information ===
Scheme:weka.classifiers.rules.ZeroR
Relation: ...

Analyzing and contrasting data mining based network intrusion detection

48 pages
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...Bayesian Network Intrusion Detection Systems (Panda & Patra, 2007). Chapter 3 provides information about data mining and its various techniques, in relation to network intrusion detection systems... ?Analyzing and Contrasting Data Mining-Based Network Intrusion Detection Systems In this modern era, computers are connected to each other using sophisticated networks. This dependence on computer networks leads to many different intrusion possibilities that threaten important data. In order to maintain the integrity of this data, it has to be secured. Electronic commerce (e-commerce) has made Internet usage a very important part in everyone’s life and has become a major means of sending and receiving...

In what ways do cognitive biases affect decision-making

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...Bayesian probability is an applicable approach that is effective in this scenario... IN WHAT WAYS DO COGNITIVE BIASES AFFECT DECISION-MAKING? Ways in which cognitive biases affect decision-makingA cognitive bias triggers a deviation in decision-making and results in unreasonable conclusions about other people and things. Subjective decisions often arise from a person’s perception of the resultant output. Cognitive biases blind a person or a group from beneficial opportunities owing to poor decision-making. Decisions often involve doubt and uncertainties that result in various cognitive biases. Even so, there are times when cognitive biases result in effective action. This paper explores ways through...

Summary a psychology experiment

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...Bayesian showed a small advantage for singletons from aspects such as repetition. Data on eye movement suggested that duplicates were... Summary of a Psychological Experiment Summary of a Psychological Experiment The article details the experiment, results, and discussion about color repetitions that pertain to the functions of the perceptual organization and attentive processes while in a visual working memory. Through the color-sharing effect, color repetitions can boost memory elements in a visual scene. It occurs because of the enhanced perceptual organization that results in reduced informational load. The effects vary in the theoretical meaning of such an impact and its use in the design of visual ...

New Keynesian Model

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...Bayesian techniques because it has additional capabilities to analyze macroeconomic issues. For example, first, it allows analysis of different consumptions between low and high income earners in a specific economy. Secondly, it can track and predict time series better than Bayesian techniques. DSGE models have been useful in identifying source of business cycles and have answered some questions concerning structural variations in the economy. This is because the model can predict impacts of economic policy changes and can establish... ?The key differences between the traditional Keynesians and the New Keynesians New Keynesian models are based on assumptions of optimizing agents andare considered basis...

You can choose a topic

2 pages
(500 words)

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...Bayesian methods for data analysis. Trends in Cognitive Sciences.
Leung, W.-C. (2001). Conducting a survey. Student BMJ, 9, 129–170.
... Marketing Introduction Marketing is a process involving planning and execution of prices, distribution and promotion of ideas, services and goods that satisfy individual needs. International marketing and business involves and ensures that needs of people and are taken into consideration. Marketing is essential strategies to win the competition from other companies and organizations providing the same product and services in the area as well as attract the target market. Marketing strategies involves the provision of promotions to major customers, media marketing...

Theories of Bayes

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...Bayesian Theory and Methods with Applications: Volume 1 of Atlantis Studies in Probability and Statistics. Springer.
Jeon, S.J. (2012). Communications to the Editor Bull. Korean Chem. Soc., 33 (1), 31-32.... Theory of Bayes Theory of Bayes The paper is aimed to explore the application of Bayes Theory on scientific study and experimentation. The chosen article was a study on the communication to the Editor Bull which was analyzed and interpreted through the use of the Bayes Theory by Seung-Joon Jeon published in 2012.
Keywords: Bayes Theory, Bayes Theorem, Bayes analysis
Theory of Bayes
The theory of Bayes by Thomas Bayes is based on the Bayes approach initiated by Richard Price which is in relation to...

Research Methods in Finance- False discoveries in mutual fund performance: Measuring luck in estimated alphas by Laurent Barras, Olivier Scaillet and Russ Wermers, The journal of Finance, 2010, 65(1), 179-216

5 pages
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...Bayesian viewpoint. Apart from giving information on management funds, this research paper review did not provide information in that they are informative. For instance, one can question how fund managers have true typical picking ability of allocating funds using the alpha distribution (Lynch and Musto, 2003). Other researchers indicated that from an investment perspective locating expert funds increases organization chances of realizing persistent achievements. Studies reviewed reveled... Research Methods in Finance Research Methods in Finance 1 Research issues in the study The paper aimed developing a simple approach that influence the false findings or reciprocated funds that display meaningful...

Managing Project

12 pages
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...Bayesian probabilistic belief. Supporting the belief of the above research scholars, Eleye-Datubo et al. (2006 and 2008) stated that network diagrams are systematic... ? Project Management Table of Contents Table of Contents 2 Task 3 Reference List-A 7 Appendices-A 8 Appendix 8 Appendix 2 9 Appendix 3 10 Introduction 12 Feasibility Study 12 Skill and Competency of Project Manager 13 Project Life Cycle 14 Project Planning 16 Project Execution and Closure 17 Conclusion 19 Reference List-B 20 Appendices-B 21 Appendix 1 21 Task 1 1. Network Diagram 2. Timing of Activities In this project, the researcher has used the concept of Earliest Start Time (EST), Earliest Finish Time (EFT), Latest Start Time (LST),...

Case Studies in Environmental Hazards. Journal Search, Article Summaries and Annotated Bibliography

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...Bayesian procedure applied in providing... Case studies in environmental hazards Case studies in environmental hazards Ebel, A. Brian & Moody, E. John. . Rethinking infiltration in wildfire affected soils. Hydrological processes, Vol. 27:1510-1517.
In this article, the authors mainly focus on the aspect of thinking about infiltration in soils that have been affected by wildfire. As such, it is mainly an article that discusses on the need to reconstruct. The authors are in the best position to write on this topic since they are both involved in research that is related to the environmental factors. They are thus well versed with the subject of wildfires and their effects on the environment. They are also k...

Management and leadership

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...Bayesian Decision making and Catastrophes. Defence Science and Technology Laboratory (DSTL) [Unpublished Report]. Available from ksglasgow@dstl.gov.uk.... ? Establishment of Business in Kava No: Establishment of Business in Kava I dreamt of becoming part of a military organization in my life and luckily, I got a chance to prove my mettle. The company intends to establish its business with strong presence in Kava. In this case, I have to incorporate the merits and demerits of starting a business in Kava along with detailed analysis of problems. Brief History of Kava-The Chosen Place for Business Kava is an island of South Pacific Region. Over 50% population comprises people who are under the age group of...

Injuries In The Workplace

3 pages
(750 words)

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...Bayesian regression analysis with linked data using mixture normal distributions. Statistical Papers, 51(2), 421-430. doi: http://dx.doi.org/10.1007/s00362-009-0208-x Kennedy, C. A., Amick Iii, B.,C., Dennerlein, J. T., Brewer, S., Catli, S., Williams, R., . . . Rempel, D. (2010). Systematic review of the role of occupational health and safety interventions in the prevention of upper extremity musculoskeletal symptoms, signs, disorders, injuries, claims and lost time. Journal of Occupational Rehabilitation, 20(2), 127-62. doi: http://dx.doi.org/10.1007/s10926-009-9211-2 Morita, J. G., Lee, T. W., & Mowday, R. T. (1993). The regression-analog to survival analysis: A...

Standard deviation in portfolio management: A look at Dubai Financial Markets Stocks

6 pages
(1500 words)

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...Bayesian Probability which is powerful tool assembled to assess stock portfolio risks (Hartman and Sprenger 216). The program generates computer... number Introduction There are many different ways and methods available to measure risk. In most financial publications, there is the common use of alpha, beta, standard deviation, Treynor, and shape ration methods (Hartman and Sprenger 37). Out of all these, standard deviation remains to be the best tool in understanding financial risks of a stock portfolio. The key idea is that when measuring the standard deviation one is able to measure the volatility of the stock. A more volatile stock is one where the stock’s returns have a higher variation from the...