There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study. Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.) Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

# Principles of Statistics

There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study. Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.) Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

Compare

4out of 5Nathan Gould–I've now read Bulmer's book twice, because I really appreciate the order and presentation of information. The chapters build on each other in a satisfying and straightforward way, with basically no wasted words or extraneous information. That said, the book is a quite dated, which is most apparent on several occasions when Bulmer refers to the tediousness of calculating certain statistical formulas by hand. His notation is also not that common anymore. These issues might be seen as a negatives if I've now read Bulmer's book twice, because I really appreciate the order and presentation of information. The chapters build on each other in a satisfying and straightforward way, with basically no wasted words or extraneous information. That said, the book is a quite dated, which is most apparent on several occasions when Bulmer refers to the tediousness of calculating certain statistical formulas by hand. His notation is also not that common anymore. These issues might be seen as a negatives if you're hoping to learn modern statistics from scratch. If you already have a foundation in modern statistics, you might enjoy these historical quirks, since it provides a window into how computation headaches shape the field of statistics. In summary, this book is adequate as an introduction to statistics, but really great if you'd like to reinforce your statistics knowledge while learning a bit about how the field evolved.

5out of 5Amit–No fluff introduction to statistics.

5out of 5Andrew–For those who understand the principles of calculus (integral & differential), I could not think of a better book to learn basic statistical theory.

4out of 5Kevin–A good book to read if you want to consolidate what you have learned in statistics. The theories are laid out in bite-sized pieces which are easy to read and follow. The exercises are nice but the problem sets are probably intended for more advanced readers. Overall, recommended for undergrad students studying Statistics.

5out of 5Iman–This is a good foundational statistics book. It does get quite complicated, especially in the later chapters. The topics that I was interested in reading over were very well presented and insightful clarifications are peppered throughout. If anything, I would give the entire 4 stars to his explanation of the laws of probability.

4out of 5Shymaa Ali–Good for people who do not know much about statistics, the book is straightforward and time saving.

5out of 5Bharadwaj Machiraju–A very good textbook to understand principles of statistics

4out of 5Haldrin–F Hi I just got your message and I will be there in about an hour and a half to get your car and your car is

4out of 5Ryan–Decent intro to stats. Math gets rather complex near the end. Will probably re-read once I have more experience and familiarity with statistics

4out of 5Marc–Overall I enjoyed this as an introduction to statistics. I had never formally covered statistics at all but been through a fair amount of calculus in college. I particularly like that it's very "dense", it gives solid and short explanations without any superfluous content. This made reading it a bit slower, but that's okay I think it will help it serve as a reference for basic statistic information in the future when I need a refresher. I took one star off because there were a couple cases whe Overall I enjoyed this as an introduction to statistics. I had never formally covered statistics at all but been through a fair amount of calculus in college. I particularly like that it's very "dense", it gives solid and short explanations without any superfluous content. This made reading it a bit slower, but that's okay I think it will help it serve as a reference for basic statistic information in the future when I need a refresher. I took one star off because there were a couple cases where a term was used that hadn't been specifically defined yet and sort of muddled my understanding until I found the specific definition, normally they were words that I kind of understood but could have used a more solid basis of how he was using them. Also there is one specific case where he changes symbol conventions for a short time but didn't note it until the end of the chapter. As a whole this book was a very solid and compact introduction to statistics for me, and its compact nature will help it serve as a reference into the future on my shelf. A knowledge of the basics of calculus would definitely be a plus if you plan on reading this as Bulmer does use the notation from calculus and a few of the techniques in the explanations.

4out of 5Xinyu–An really good book in introduction on statistics. It explains really well on those statistical concepts, which otherwise can be quite confusing. Though it's a introductory book, I can't say that I understand it all. I feel I need more time and more experience in fully understanding the concepts and rationales. An really good book in introduction on statistics. It explains really well on those statistical concepts, which otherwise can be quite confusing. Though it's a introductory book, I can't say that I understand it all. I feel I need more time and more experience in fully understanding the concepts and rationales.

4out of 5Eric Pecile–An excellent guide for the statistician on the significance of variables and the meaning of various distributions. Written very clearly, this is a great reference for anyone handling quantitative data. It falters slightly as it is very much a guide for those with an existing degree of statistical training rather than an introductory guide as one may accidentally infer from the title.

4out of 5Sefa–Good refresher/reference book for readers who are already familiar with concepts of statistics. Covers a ton of concepts well, with historical anecdotes, in a relatively small volume. Probably not the best book for an introduction to statistics.

5out of 5Neil Rempel–A text book,

5out of 5Molo–its ok

4out of 5Bellamy–great!

5out of 5Waleed Saber–5out of 5Sabitha–4out of 5Human Morad–5out of 5Naciima Y–5out of 5Jay Almoite–4out of 5Alon Friedman–5out of 5Stu–4out of 5Ismail–5out of 5Avery–4out of 5Wonda Grobbelaar–4out of 5Ali–5out of 5Umasankar Hemmanur–5out of 5Sylvia Kaburu–5out of 5Onias–