Rating: 
Summary: Excellent in its day - but that day has passed
Review: At the time of its debut (1958) this book was viewed as a fairly advanced treatment of probability and math stat. While it has been updated over the years, it has not kept pace with the rapid changes in the field. (Craig died in 1978!). For those with a bit integral of calculus (it is a math stat book), it is good for review and has some excellent problems (but any answers in the back of the book are simply numeric answers with no explanations). For the right class, it still could be a really good intro to math stat. Be warned - this book gives you nothing in the way of measure and probability but if you can buy it used and cheap, it is well worth having.
Rating:
Summary: Excellent in its day - but that day has passed
Review: At the time of its debut (1958) this book was viewed as a fairly advanced treatment of probability and math stat. While it has been updated over the years, it has not kept pace with the rapid changes in the field. (Craig died in 1978!). For those with a bit integral of calculus (it is a math stat book), it is good for review and has some excellent problems (but any answers in the back of the book are simply numeric answers with no explanations). For the right class, it still could be a really good intro to math stat. Be warned - this book gives you nothing in the way of measure and probability but if you can buy it used and cheap, it is well worth having.
Rating: 
Summary: book I used at Maryland
Review: Hogg and Craig is one of my favorite texts. It is an intermediate text in mathematical statistics similar to Mood, Graybill and Boes. I took qualifying exams in mathematics for my Masters Degree in math at the University of Maryland in the early 1970s. One of the exams I took was in statistics. I had little formal training in statistics at the time. Hogg and Craig was the recommended text for the statistics exam. So I bought it and studied out of it on my own. It was very clear with excellent coverage of methods for deriving distributions for random variables and transformations of random variables. I passed my exams and got my highest grades on the statistics exam even though I had more training in abstract algebra. Hogg and Craig really helped. It has been revised since then to maintain currency with statistical developments but it still has maintained its clarity and usefulness.
Rating:
Summary: book I used at Maryland
Review: Hogg and Craig is one of my favorite texts. It is an intermediate text in mathematical statistics similar to Mood, Graybill and Boes. I took qualifying exams in mathematics for my Masters Degree in math at the University of Maryland in the early 1970s. One of the exams I took was in statistics. I had little formal training in statistics at the time. Hogg and Craig was the recommended text for the statistics exam. So I bought it and studied out of it on my own. It was very clear with excellent coverage of methods for deriving distributions for random variables and transformations of random variables. I passed my exams and got my highest grades on the statistics exam even though I had more training in abstract algebra. Hogg and Craig really helped. It has been revised since then to maintain currency with statistical developments but it still has maintained its clarity and usefulness.
Rating:
Summary: Didn't like this too much
Review: I think Meyer's book: Introduction to Probability and Statistical Applications that is on probability distributions and basic probability theory is easier to understand but that was my first introduction to using the integral a lot. But this Mathematical Statistics book we covered in two terms later in my school/math career after having some experience in goverment statistics work. I had trouble with the term work taken from this book. But I was able to score B in the exams in these courses by studying hard from the book itself, not much else, besides some biographies/histories of the statisticians themselves. The professors that use this book generally don't stray from the book too much. The second half of the book in our courses is not done linerarly. I will be repeating the courses this year on the way to grad school. I don't find it that hard to read when I put in the time. At other times it seems very Greek and dry. It is a very slow read but then that's science for you. I am developing a word processed file with all the answers to the text's problems for my own use. Certainly I understand that outcomes of experiments is the subject of the book. I also see how the book does the math ground work behind applied statistics. But is this the real world? It seems like psychology it does not make common sense. Mathematically the book takes some proper preparation. But as one math book I have worked through and will work through again this year I am impressed.
Rating: 
Summary: U can do much better
Review: I took a full year course based on this text. I found it was terse, dated and poorly worded. The explanations of key topics where long winded, meandering and ultimately muddled. The material in each section was rarely of value when confronted with at least half the sections problems. I felt that there should have been more examples that cut to the meat of the problem(such as MLE) showing the mechanics of the solution and giving general strategies to solve real world problems using that technique. I feel that statistics and mathematics is best learned by doing lots of problems and in the case of statistics practicing on real world data. Detailed solutions done by the masters can also go along way to help improve ur analytic skills. I feel this book does not have either feature, covers the modern topic mathematical statistics poorly and should not be used unless the user has severe masochistic tendencies.
Rating: 
Summary: Introduction to Mathematical Statistics by Hogg and Craig
Review: I worked with an earlier version of this text. The text is
geared for math majors. There are many practical examples;
however, the more theoretical examples are elusive at best.
Coverage of the basic laws of probability is good. The examples
dealing with continuous random variables require some prior
knowledge of intermediate calculus which should be no problem
for math majors or engineers. The book benefited me when I
took and passed the Fundamentals of Engineering Examination.
In addition, I've taught statistics several times.
This work is geared for the above-average student. In some
areas, it could be supplemented with the Schaum's Statistics
Outline.
Rating:
Summary: Old school textbook.
Review: One of those little monochrome bound textbooks from the 1960's that you wish had never been written (i.e. the book explains statistical methods using mathematical jargon and symbols). Unless you are a math major, who communicates in these terms, steer clear.
Rating:
Summary: Old school textbook.
Review: One of those little monochrome bound textbooks from the 1960's that you wish had never been written (i.e. the book explains statistical methods using mathematical jargon and symbols). Unless you are a math major, who communicates in these terms, steer clear.
Rating:
Summary: Not a good book.
Review: This book is currently required for my intro. to stats course. I have found this book to be of no help at all. It breifly discusses the subjects with little or no structure; requiring you to use other references constantly.(Never a good idea in math where notation is almost never consistent!) Theorems/definitions are unclear and un-highlighted. Possibly the most frustrating aspect is the examples. Examples are given without even posing a question and the "solutions" to the examples are done with very little explanation or methodology. Also, the examples seem to be much easier than the excersises which have only a limited number of answers in the back of the book. I feel the text does not come close to preparing the reader for the excercises. As another reviewer suggested, this book could be useful to someone with experience and background in statistics, but for an introductory course, the book leaves out too many background details that it assumes the readers know. I am sure there are much better introductory books.
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