Bayesian statistics

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    this essay, we present a discussion about Bayesian methods in Spatial Statistics. Bayesian methods are approaches to statistical inferences which have been around for several decades and are also used in Geographic Information Systems. The application of these methods in practical problems has increased significantly within the last few years due to recent advances in tools for computation and simulation [1]. At the heart of any Bayesian data analysis method are the likelihood function, which expresses information about the parameters in the data and the prior distribution, which quantifies the belief about the parameters before measurements. The prior distribution and likelihood function can be multiplied together to form a proportion to the posterior distribution which represents knowledge about the unknown parameters after the data has been observed [3]. We begin with an introduction to the basic steps in Bayesian analysis followed by defining the important terminologies in Bayesian methods which are “prior and posterior distributions” and “Markov-Chain Monte Carlo methods.” This is followed by explanation on how Bayesian perspective can be considered as a unified framework to view uncertainty. Finally, we present a comparison between Bayesian methods and the classical ' 'frequentist ' ' statistical methods.…

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    Finally, I decided to research on Bayesian adaptive clinical trials. Unlike conventional clinical trials have substantial uncertainty in intervention arms (e.g. uncertainty in optimal dose/duration), adaptive clinical trials allow us to modify key trial parameters as we are acquiring more information during the experiments, thus reducing the uncertainty and speeding up the evaluation of interventions. Also, adaptive clinical trials allow for dropping arms that do not work well during the…

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    I am M. Patricia Cifuentes, a postdoctoral researcher at Ohio State University, appointed by the College of Public Health and Biomedical Informatics. I am an MD specialized in statistics with a doctoral degree on Public Health. I contact you to share some research ideas I propose in the context of my application to the Yerby postdoctoral fellowship program for which I suggested you as faculty mentors. The proposal I presented consists on developing theory-based and data-driven models of health…

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    two years studying physics, I dedicated to get my bachelor 's degree in statistics as soon as possible. Therefore, I became the first student who completed his bachelor 's degree successfully in six semesters which took three years. My professors, friends and family was proud of their outstanding student, friend and…

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    methodology. The authors concentrated on the causal discovery of networks and the techniques of using Bayesian networks. Furthermore, they discussed the utilisation of this methodology for causal modelling. This source is important at the initial stage of the project as it contributes to the decision-making process at the modelling technique selection stage. However, it is not as important as the other two sources after it was decided not to be used as the modelling method for the system model…

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    In the book “the Signal and the noise”, author Nate Silver talks about prediction from many different angles. Silver explains how prediction is a part of our everyday life and how it affects us. From math to history, inside of a class room or on a court/field, prediction is something we deal with on a day to day basis unconsciously. Silver talks about the benefits of failure and how failure is helpful in the long run with making predictions. Throughout the years we have made progress with…

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    probability plot and histogram. If all the residuals are not within two standard deviations in the normal probability plot or form a bell curve in the histogram, then they are not normally distributed. When the residuals are not normally distributed, it means the residuals a have pattern in them (i.e. serial correlation or heteroscedasticity). Possible fixes are changing the model and getting better data. Problem 2: The residuals should not be serially correlated. This can be seen visually by…

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    1. a. The data set consist of 44 female and 53 males. b. There are 21 people under the age range of 13-35, which account for 21.6% of the total 97 in the sample. c. The mean level of the hour spent in the office during week 2 is 47.47 hours, with the standard deviation of 17.06. The distribution is slightly negative skew (-0.237), although in an acceptable range suggest that slightly more samples spend more hours in office than the average. The distribution’s value for kurtosis (-1.005)…

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    Introduction Antibiotics were initially thought of as a superior drug that could kill many bacterial diseases. Prior to antibiotics, it was hard for anyone to fight a bacteria. However, bacteria are very changing and have begun being able to gain resistance against antibiotics due to overuse, not strong enough dosage of antibiotics, or improper use. By determining the resistance and cross-resistance, one may determine the the relative ability for bacteria to gain resistance to antibiotics. We…

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    Metabolism is a complex process in organisms that convert the food into energy for organism to function properly. Metabolic rate is typically defined as the amount of energy the organism is currently using to maintain the activity (Perkin, 2015). Since metabolism is a key in sustaining the organisms’ life, we decided to investigate the experiment about metabolic rate caterpillar, Manduca sexta. There are many techniques used to measuring the metabolic rate, but there are only best method that…

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