Ebook Info
- Published: 2006
- Number of pages:
- Format: PDF
- File Size: 3.26 MB
- Authors: F.M. Dekking
Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
User’s Reviews
Reviews from Amazon users which were colected at the time this book was published on the website:
⭐This book reads easily because it gives many concrete examples and uses a tutorial approach to teaching. However, you still need to know some math! You don’t need a math degree. A good first course in calculus covering derivatives and integrals, including logs and exponentials, and some introductory combinatorics (basic knowledge of sets, permutations and combinations) is enough. Any sophomore or, at the latest, junior majoring in engineering or hard science has the prerequisites.An understanding of probability is necessary for understanding statistics, so the first half of this book is probability. Without probability, statistics becomes something like “here are some facts, trust me, now here are some formulas, recipes and tables and you will learn when to use each one”. For many people this may be enough, especially if they just need to get something done. But if you want to know why hypothesis testing is done the way it is and how it works, buy this book. For example, many statistics books just assume a normal distribution for sampling and the only thing you need to learn is when to use a one-tailed or two-tailed test and which formula to use. This is valid when working with sufficiently large populations or samples. In contrast, the worked example in this book does not use a normal distribution and it walks you through the reasoning and calculation. The reasoning is applicable to any population and distribution. When you change to a normal distribution the principles remain the same, only the formulas change. You learn the principles.Now to the book’s style. This is a tutorial style book that teaches using examples. It doesn’t skip many steps and can feel somewhat chatty. It repeats simple calculations along the way so you don’t have to page back and find where that number was calculated. This keeps the flow going. Learning by example is actually a good way to learn if you are new to the material. Some however, may not like this style, so read some online first before buying. If you already have probability under your belt and are up on your math then you may find this book slow going. This book is aimed at scientists and engineers, so if you are looking for a rigorous math book with proofs, look elsewhere.Summary: If you’ve got the prerequisites then this is a great book for self teaching at a good price. If you are lacking in math and you need to do statistics now, then pick up a “cookbook” statistics book and come back later when you have the math background. If you know your stuff and need a reference, look elsewhere.This textbook is the best reference for learning the foundational concepts of probability theory. I am a graduate engineering student in robotics and control theory. Over the course of my education, I had training in probability theory, but I only had only preserved unstructured intuition of probability concepts. This book builds the concepts in a very effective order allowing the reader to grasp various concepts and how they are related, e.g., definitions of probability and conditional probability, discrete and continuous random variables, and single and joint probability distributions.Further, the material exposition in this textbook is superb. It uses simple language, yet rigorous, and it uses concise examples in the explanation. Also, there are short questions in the text with solutions at the end of each chapter to help the reader test their knowledge during reading. There are also additional questions at the end of the chapter.Finally, I would also add this is the perfect book for self-study.I have a strong general background in math, but not in probability and statistics. I use this book for self-study, and I find that it fits that purpose excellently. There are plenty of examples, and problems are adjusted so that they focus more on principles and understanding rather than on grunt-work calculations.My main objection, and the reason for giving it 4 stars, is English language. I am not a native English speaker, and it’s obvious that none of the authors is either. Even worse, I encounter at least one misleading, or hard to understand sentence per chapter (mostly among problems). The book most definitely needs proofreading and language corrections!We used this book in our Introduction to Probability course at Georgia Tech. This book is written in a not-so-easy to understand matter and is good for someone that has a strong background in math. A few of my friends doing their Ph.D were helping me with this course and they also found this book hard to understand as well. If you read the text you’re still gonna have such a hard time doing the exercises because it doesn’t explain everything smoothly. I searched through the internet to find a solution manual for this book and simply they don’t have it. You only get the solution if you get the teacher version. The book is written and published in Netherlands and it doesn’t have any online resource for students. If you have to buy this book for your class make sure you get “Schaum’s Outline of Probability, Random Variables, and Random Processes” or a similar book for extra help, otherwise you’ll regret like I do.Fantastic overview of modern methods. I especially appreciated the discussion on estimators.This book is well-written. It connects probability theory and statistical inference seamlessly. I have used this book for self-study and learned a great deal from it. I would like to suggest those who want to explore the exciting filed of statistics read it thoroughly and practice all those computation examples using the software R.This book has amazing examples and practice questions. I’m grateful to have had it for my probability course. Excellent buy.One of the worst engineering textbooks I’ve ever used. It’s written like a novel – the formulas are not boxed in, the key terms aren’t bold. It’s not the book you want to study a complex topic.Great book, well prices. I used it in college then bought it for my own use and it’s great for anyone who has a good understanding of mathsGood book. Easy to understand. My lecturer was unspeakably poor. I got 90% by forgetting everything he said and reading this book.This book does exactly what it promises in the title. The contents start from plain probability spaces, get soon to random variables and independence, and then go the fundamental theorems of statistics. The overall trip is therefore from probability to arrive to statistics as things should be. The language keeps always simple and plain to ease full intuition, yet definitions and Mathematics is rigorous. So the book gives an excellent support for self-study.Finally the size of the text keeps also reasonable, exactly enough to contain the necessary stuff, avoiding to become one of those 600 pages bricks. The only aspect which is not comparable with the level of the book are some examples, which occasionally are uselessly complicated compared to the purpose they were meant (e.g. the “jury valuation” in the Simulation chapter). This minor point does not reduce the optimal mark for this book that, for its qualities, has no obvious competitor.Good book for starting study statistics: in the book are covered the basic topics of descriptive analysis, probability and inference. The books has been delivered in perfect conditions and it has been delivered in less time than expected (1 day before).Book is generally in good condition. I am happy with this . Thank you very much!
Keywords
Free Download A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) in PDF format
A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) PDF Free Download
Download A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) 2006 PDF Free
A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) 2006 PDF Free Download
Download A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics) PDF
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