Probability And Bayes Theorem For Beginners
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| 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.
| 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 | : Therese M. Donovan |
| Publisher | : Oxford University Press, USA |
| Total Pages | : 430 |
| Release | : 2019 |
| Genre | : Mathematics |
| ISBN | : 0198841299 |
This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.
| 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 | : 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 | : 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 | : Chris Ferrie |
| Publisher | : Sourcebooks, Inc. |
| Total Pages | : 26 |
| Release | : 2019-07-02 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1728213517 |
Fans of Chris Ferrie's Rocket Science for Babies, Astrophysics for Babies, and 8 Little Planets will love this introduction to the basic principles of probability for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. If you took a bite out of a cookie and that bite has no candy in it, what is the probability that bite came from a candy cookie or a cookie with no candy? You and baby will find out the probability and discover it through different types of distribution. Yet another Baby University board book full of simple explanations of complex ideas written by an expert for your future genius! If you're looking for baby math books, probability for kids, or more Baby University board books to surprise your little one, look no further! Bayesian Probability for Babies offers fun early learning for your little scientist!
| Author | : Arthur Taff |
| Publisher | : |
| Total Pages | : 78 |
| Release | : 2019-07-16 |
| Genre | : Computers |
| ISBN | : 9781925997583 |
The Perfect Book for Beginners Wanting to Visually Learn About Bayes Theorem Through Real Examples! What if you could quickly and easily learn Bayesian data analysis without complex textbooks and statistics classes? Imagine being able to apply your newly learned theory to real life situations! Multi-time best selling IT & mathematics author, Arthur Taff, presents the perfect guide for any beginner. Bayesian data analysis can be difficult to learn, especially through textbooks and statistic classes at school. This book aims to solve that issue by presenting the theories in an easy-to-understand and visually intuitive way. This book contains a number of visual examples to build a basic understanding of Bayesian data analysis and then works to teach at a deeper level without the complexities you'd see in other similar books. Additionally, every example in this book has been solved using Excel. In this book, you will get: A Basic Introduction to Bayes Theorem (with examples) - The initial introduction demonstrates how Bayesian data analysis works when you have a single new piece of data to update initial probabilities. Adding New Data & Updating Probabilities - Takes the above example and looks at what happens if we have multiple pieces of data instead of a single piece. Bayes Theorem Terminology - The formal names for the different parts of the Bayes Theorem equation, and how it all comes together for an easier overall understanding. How to Deal With Data Errors - In a real life situation, it is unlikely that your data will be error-free. This section shows you how to deal with those errors and still get accurate probability estimates. Arthur's personal email address for unlimited customer support if you have any questions And much, much more... If you are a person that learns by example, especially visually, then this book is perfect for you! It is a very important topic in a wide range of industries - so dive in to get a deep understanding! Well, what are you waiting for? Grab your copy today by clicking the BUY NOW button at the top of this page!
| Author | : Andy Hayes |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 118 |
| Release | : 2017-01-11 |
| Genre | : |
| ISBN | : 9781542493598 |
Bayes theorem - A Quick-start Beginner's Guide Applications of the theorem are widespread and not limited to the financial realm. As an example, Bayes' theorem can be used to determine the accuracy of medical test results by taking into consideration how likely any given person is to have a disease and the general accuracy of the test. Bayes' theorem gives the probability of an event based on information that is or may be related to that event. The formula can be used to see how the probability of an event occurring is affected by new information, supposing the new information is true. For example, say a single card is drawn from a complete deck of 52 cards. The probability the card is a king is four divided by 52, or approximately 7.69%, since there are four kings in the deck. Now, suppose it is revealed the selected card is a face card. The probability the selected card is a king, given it is a face card, is four divided by 12, or approximately 33.3%, since there are 12 face cards in a deck. Take Action Today and Learn Bayes Theorem in no time! Click the "Buy now with 1-Click" to the right and get this guide immediately.
| 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
