Bayes Theorem Examples
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| Author | : Dan Morris |
| Publisher | : Independently Published |
| Total Pages | : 112 |
| Release | : 2016-10-02 |
| Genre | : Bayesian statistical decision theory |
| ISBN | : 9781549761744 |
***** #1 Kindle Store Bestseller in Mathematics (Throughout 2016) ********** #1 Kindle Store Bestseller in Education Theory (Throughout 2017) *****If you are looking for a short beginners guide packed with visual examples, this book is for you. Bayes' Theorem Examples: A Beginners Visual Approach to Bayesian Data Analysis If you've recently used Google search to find something, Bayes' Theorem was used to find your search results. The same is true for those recommendations on Netflix. Hedge funds? Self-driving cars? Search and Rescue? Bayes' Theorem is used in all of the above and more. At its core, Bayes' Theorem is a simple probability and statistics formula that has revolutionized how we understand and deal with uncertainty. If life is seen as black and white, Bayes' Theorem helps us think about the gray areas. When new evidence comes our way, it helps us update our beliefs and create a new belief.Ready to dig in and visually explore Bayes' Theorem? Let's go! Over 60 hand-drawn visuals are included throughout the book to help you work through each problem as you learn by example. The beautifully hand-drawn visual illustrations are specifically designed and formatted for the kindle.This book also includes sections not found in other books on Bayes' Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). - For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios. A few examples of how to think like a Bayesian in everyday life. Bayes' Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. Learn how Bayes can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes' Rule. - Bayes' Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700's to its being used to break the German's Enigma Code during World War 2. Fascinating real-life stories on how Bayes' formula is used everyday.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. An expanded Bayes' Theorem definition, including notations, and proof section. - In this section we define core elementary bayesian statistics terms more concretely. A recommended readings sectionFrom The Theory That Would Not Die to Think Bayes: Bayesian Statistics in Pythoni> and many more, there are a number of fantastic resources we have collected for further reading. If you are a visual learner and like to learn by example, this intuitive Bayes' Theorem 'for dummies' type book is a good fit for you. Praise for Bayes' Theorem Examples "...What Morris has presented is a useful way to provide the reader with a basic understanding of how to apply the theorem. He takes it easy step by easy step and explains matters in a way that almost anyone can understand. Moreover, by using Venn Diagrams and other visuals, he gives the reader multiple ways of understanding exactly what is going on in Bayes' theorem. The way in which he presents this material helps solidify in the reader's mind how to use Bayes' theorem..." - Doug E. - TOP 100 REVIEWER"...For those who are predominately "Visual Learners", as I certainly am, I highly recommend this book...I believe I gained more from this book than I did from college statistics. Or at least, one fantastic refresher after 20 some years after the fact." - Tin F. TOP 50 REVIEWER
| Author | : James V. Stone |
| Publisher | : Sebtel Press |
| Total Pages | : 170 |
| Release | : 2013-06-01 |
| Genre | : Mathematics |
| ISBN | : 0956372848 |
In this richly illustrated book, a range of accessible examples are used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis.
| Author | : Donald Stan |
| Publisher | : |
| Total Pages | : 38 |
| Release | : 2019-07-09 |
| Genre | : |
| ISBN | : 9781079478525 |
Bayes theorem is a method that is used to solve conditional probability, Bayes theory is accurately that is given you the actual probability of an event given information about the testThis book is loaded with interactive examples no bayes theoremBayes theorem is also called Bayes theory, Bayes rule or Bayes formula and is used in different industries including spam filters and drug testing due to the fact that it is vital to provide a systematic and proven ways to find the estimated probability when new data is available Bayesian data analysis is thought in statistics but not taught in a practical way, this book will show you a very comprehensive understanding on how Bayesian statistics functions, it contains practical Bayes Theorem examples to help increase your understanding of bayes theoryThis book will show you Bayes theorem works in real life and how it can be applied to real life applicationGet your copy today and understanding the basics of Bayes theorem and its application in a wide range of industries
| Author | : Peter M. Lee |
| Publisher | : Wiley |
| Total Pages | : 352 |
| Release | : 2009-01-20 |
| Genre | : Mathematics |
| ISBN | : 9780340814055 |
Bayesian Statistics is the school of thought that uses all information surrounding the likelihood of an event rather than just that collected experimentally. Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee’s well-established introduction maintains the clarity of exposition and use of examples for which this text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS (Bayesian Inference Using Gibbs Sampling) as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modelling and Bernardo’s theory of reference points.
| Author | : Robert Collins |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 52 |
| Release | : 2017-06-21 |
| Genre | : |
| ISBN | : 9781547270385 |
This book is a discussion about the Bayes' Theorem. The first part of the book helps you understand what Bayes' Theorem is and the areas in which it can be applied. The derivation of Bayes' Theorem is also discussed, so you will know the various steps it takes for you to derive Bayes' Theorem. Some basic examples are then given to help you understand how you can solve them by use of Bayes' Theorem. These examples have been picked from a wide range of areas, and they are all based on the concept of conditional probability. This is a situation in which you are given the evidence and you are expected to calculate or determine the probability of a certain event occurring, or in other words, if an event A has occurred, what is the probability that event B will occur. The application of Bayes' Theorem in drug and medical tests is then discussed in detail. You will learn how to determine the probability of individuals being users of a certain drug or non-users of that drug. You will also learn how to determine the probability of individuals having certain conditions. The book also discusses the application of Bayes' Theorem when you are rolling dice. You will learn how to apply this Theorem to determine the probability of getting Heads and Tails. The book also helps you in determining if a coin toss is fair or not based on the outcome after it has occurred. Here is a preview of what you'll learn: - What is Bayes Theorem? - Basic Examples - Drug and Medical Tests - Dice and Rolls - Is the Coin Fair?
| Author | : Will Kurt |
| Publisher | : No Starch Press |
| Total Pages | : 258 |
| Release | : 2019-07-09 |
| Genre | : Mathematics |
| ISBN | : 1593279566 |
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.
| Author | : Lee Baker |
| Publisher | : Lee Baker |
| Total Pages | : 30 |
| Release | : |
| Genre | : Medical |
| ISBN | : |
Bayes’ Theorem is hard. Is it, though? If you flick through any of the other books on Bayesian statistics you’ll get the distinct impression that you’ll have a lot of really hard maths to do, and it can be really intimidating. But is that what Bayesian stats is really all about? If you’re wondering whether you should have a look at Bayesian statistics to see if it’s right for you, then Bayes’ Theorem and Bayesian Statistics in the Getting Started With Statistics series is your first port of call. If what you need is a short guide to getting started, a snappy little non-threatening introduction to Bayes’ Theorem and Bayesian Statistics that dispels the biggest myths, answers the most frequently asked questions and inspires you to take the next steps in your journey, then look no further. Bayes’ Theorem and Bayesian Statistics is that guide. This book is not written for statisticians. Nor is it written by a statistician. A Physicist by trade, and a self-taught statistician, I may have worked (and taught) as a statistician for several years but I have my own struggles with statistics, so I understand where the hard bits are. Better still, I know how to explain them to others in plain English without using difficult to understand technical terminology. That’s what you can expect in this book. First, I’ll explain what Bayes’ Theorem is in simple terms. Then you’ll move on to understanding what conditional probability is and why you don’t need it if you want to find a parking spot, but you do if you’re playing cards (and you want to win). You’ll learn about Prior and Posterior probabilities, and use them to work out if you need to take a brolly to the beach with you (spoiler alert – I live in Scotland. I always need to take a brolly to the beach!). Then I’ll bust a few myths about what Bayesian statistics is – and what it isn’t. By this point you’ll have made up your mind about whether you want to go further, so I’ll show you how to take your next steps. Bayes’ Theorem and Bayesian Statistics makes no assumptions about your previous experience and is perfect for beginners and the Bayes-curious! Discover the world of Bayes’ Theorem and Bayesian Statistics. Get this book, TODAY!
| Author | : Sharon Bertsch McGrayne |
| Publisher | : Yale University Press |
| Total Pages | : 336 |
| Release | : 2011-05-17 |
| Genre | : Mathematics |
| ISBN | : 0300175094 |
"This account of how a once reviled theory, Baye’s rule, came to underpin modern life is both approachable and engrossing" (Sunday Times). A New York Times Book Review Editors’ Choice Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the generations-long human drama surrounding it. McGrayne traces the rule’s discovery by an 18th century amateur mathematician through its development by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—while practitioners relied on it to solve crises involving great uncertainty and scanty information, such as Alan Turing's work breaking Germany's Enigma code during World War II. McGrayne also explains how the advent of computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security. Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.
| Author | : Logan Styles |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 100 |
| Release | : 2016-07-08 |
| Genre | : |
| ISBN | : 9781535194594 |
Discover how to use Bayes' Theorem for real world applications like weather prediction, criminal investigation, blackjack games, and countless others! Picture this... You've been feeling sick for a couple days. You have a job interview on Thursday. Today is Monday, and you want to make sure you're healthy by Thursday...but you can't afford the time or cost of seeing a doctor before then. What are the odds of being up and running by Thursday? Do they get better if you've just started a new health kick? Or do they stay the same? Or perhaps... ...you notice your good ol' dog Spike walking clumsily and think he may be going blind. However you can't take him to a vet immediately...but you still want to know what the odds are that something's wrong with his eyes. So how do you determine this? These questions and countless others can be better answered when you apply Bayes' Theorem. To simplify it, Bayes' Theorem is the method by which you use to determine the probability of an event based on conditions that may be related to an event. So if you want to determine if your dog is sick and you know his breed is a golden retriever...well you could possibly use that information to assess the likely odds of him being sick! In this guide you'll see example after example of Bayes' Theorem being put into practice. You'll also see how each conclusion is arrived at with summation notation and basic equations. BUT...the purpose of this book isn't just to throw equations at you. It's to help you get an intuitive feel for the probability of an outcome without having to plug in all the numbers. I made sure this book wasn't filled with too much jargon or advanced notation. In fact, this book can be used if...1. You're just a lay person interested in learning how to "predict" the chances of events and gain deeper insight to the world around us2. You're a student who needs to learn about Bayes' Theorem quickly and easily3. You're a teacher or educator looking to advance or brush up on your existing knowledge of Bayes' Theorem I encourage you to download 'Bayes Theorem' so you can make more informed approximations of how events will play out. Plus, when you download "Bayes Theorem", you'll also discover: How to solve unobvious questions How to do your own genetic testing (find out if you're more prone to certain types of ailments) Why a smoker and non-smoker may have equal chances of developing chronic bronchitis How companies can use Bayes' Theorem to manipulate and spew propaganda What the chances are of someone becoming addicted to pills How to determine if a suspected criminal is more likely innocent or guilty The proper mathematical equations and notation to use-and guided explanations of each So download 'Bayes Theorem' today and enhance your statistical knowledge on the world and how things work
| Author | : Thomas Laville |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 112 |
| Release | : 2017-10-29 |
| Genre | : |
| ISBN | : 9781979267694 |
Thinking of learning Probability and Bayes Theorem? Then you have landed in the right place. If you want to well understand Bayes theorem as well as apply its principles, you must first master the concept of probability. Probability is the likelihood that something will happen, describing such things as the chances of you drawing a specific card, say an ace, from a deck of playing cards. There are a simple ways to calculate such probabilities using the information you have in front of you, however Bayesian probability takes this one step further by incorporating previously known information to inform these calculations. Probability and Bayes theorem is present everywhere in many of the different things that we carry out throughout the day, such as Googling the internet, applying spam filters, machine learning, and so much more. This book aims to help build a foundation for the understanding of Bayes' theorem using a step-by-step method that introduces the various elements of probability before approaching the theorem itself. Understanding these sometimes rather complex concepts is made very easy with the use of several examples and everyday applications of probability. You will find that being in possession of a solid understanding of the ideas related to and applications of both probability and Bayes theorem in particular will assist you in comprehending and indeed engaging with some of the ways that these concepts are used today, including practical examples like "We want to go for a picnic but it is cloudy. Is it likely to rain?" or "What are the chances that someone has an allergy?" or even "In a zombie apocalypse, how likely is my test kit to determine whether someone is really infected?." This book will help you explore exactly what Probability and Bayes Theorem are and will introduce the reader the concepts, applications and practical case studies. By the time you are done reading this book, you will have a complete understanding as to how to measure probability and how Bayes Theorem works. Following are the important points discussed in this book: What is a Probability? Overview of Probability Basics in Set Theory Axioms and Rules of Probability Use a Tree to calculate Probabilities Probability with Combinations And Permutations Formulas Probability Distribution Conditional Probability Bayes' Theorem Book Objectives To have a right understanding of Probability and Bayes Theorem and their fundamental principles. To have an elementary understanding of (some of the) more advanced topics such as Naive Bayes Method in Machine Learning Target Users This book designed for a variety of target audiences. The most suitable users would include: Newbies in statistics and Probability Professionals in Data scientist and Social Sciences Professors, lecturers, or tutors to be in position to find better ways to explain the content to their students with simples and easiest way The students and Academicians, especially those that are focusing on Bayes Theorem, Computer Sciences and Statistics as their professions Therefore, what are you waiting for; let us start delving into the fascinating and useful world of probabilities! Scroll to the top and click on 'buy now' to get started.
