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Mathematical Statistics With Applications
 
 

Mathematical Statistics With Applications [Hardcover]

Dennis Wackerly (Author), William Mendenhall III (Author), Richard L. Scheaffer (Author)
3.3 out of 5 stars  See all reviews (42 customer reviews)


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Book Description

0534209165 978-0534209162 September 21, 1995 5th
Intended for the two-term mathematical statistics course offered in mathematics and statistics departments (calculus prerequisite), this book includes:
-- Emphasis on inference as the sole dominating purpose of the course with probability presented in the context of inference, not as an isolated subject
-- A strong introductory chapter that describes the purpose of statistics and its role in scientific research
-- An increased number of excellent exercises based on practical application and real data
-- Improved presentations of regression, experimental design, and order statistics


Editorial Reviews

About the Author

Richard L. Scheaffer, Professor Emeritus of Statistics, University of Florida, received his Ph.D. in statistics from Florida State University. Accompanying a career of teaching, research and administration, Dr. Scheaffer has led efforts on the improvement of statistics education throughout the school and college curriculum. Co-author of five textbooks, he was one of the developers of the Quantitative Literacy Project that formed the basis of the data analysis strand in the curriculum standards of the National Council of Teachers of Mathematics. He also led the task force that developed the AP Statistics Program, for which he served as Chief Faculty Consultant. Dr. Scheaffer is a Fellow and past president of the American Statistical Association, a past chair of the Conference Board of the Mathematical Sciences, and an advisor on numerous statistics education projects. --This text refers to an out of print or unavailable edition of this title.

Product Details

  • Hardcover: 816 pages
  • Publisher: Duxbury Pr; 5th edition (September 21, 1995)
  • Language: English
  • ISBN-10: 0534209165
  • ISBN-13: 978-0534209162
  • Product Dimensions: 9.2 x 7.6 x 1.3 inches
  • Shipping Weight: 2.8 pounds
  • Average Customer Review: 3.3 out of 5 stars  See all reviews (42 customer reviews)
  • Amazon Best Sellers Rank: #724,424 in Books (See Top 100 in Books)

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Customer Reviews

42 Reviews
5 star:
 (13)
4 star:
 (7)
3 star:
 (9)
2 star:
 (6)
1 star:
 (7)
 
 
 
 
 
Average Customer Review
3.3 out of 5 stars (42 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

23 of 24 people found the following review helpful:
2.0 out of 5 stars Anything but Wackerly, February 19, 2007
This is an adequate text up until chapter 6. The probability chapter the the discrete probability distributions are great. The concepts and derivations are logically laid out and make sense. Things begin to get frustrating in chapter 4 and really fall apart after chapter 6. After chapter four the author no longer tries to put anything in context. He derives very little and simply states long, cryptic formulas and expects the reader to magicaly understand the big picture and fill in the gaps on their own. He skips over the over 200 years of the development in statictical theory and simply states the results and the student is expected to fill in the gap. The most self evident properties are expounded on in the chapters and the most important and subtle properties are hidden in the exercises or neglected altogether. I am nearly finished with my undergraduate degree in applied mathematics and am mathematicaly mature. I am comfortable with both applied and pure/proof-type mathematics and this text makes my stomach turn. It makes me want to reconsider my major. I am giving this text 2 stars simply because the first 5 chapters are adequate. If you just need a course in probability, this might be the text for you. If you need to move on to statistical inference and you need the big picture/contextual background explained rather than pluging and chuging blindly with nonsensical formulas, then this is not the text for you. Way to drop the ball, Wackerly!
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16 of 18 people found the following review helpful:
4.0 out of 5 stars My goto stats book, May 10, 2006
By 
This has been my goto stats book since I bought it for a class in 2002. It's a clear introduction to mathematical statistics. I use it to try to understand some of the more advanced concepts that I'm learning now, but, unfortunately, it is just an introductory book. It does have a lot of information in it, so I still rely on it pretty heavily.

On the flip side, I'm using this book less and less because I bought Wasserman's 'All of Statistics', which is much more compact and has far more concepts in it. 'All of Statistics' is more of a reference tool, instead of a learning tool, though.

If you want to learn statistics, pick up this book and Ross's First Course in Probability. For most non-specialists these books will contain all the probability and statistics you will ever need.

Sorry I can't recommend anything cheaper.
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22 of 26 people found the following review helpful:
4.0 out of 5 stars Good reference book overall, January 15, 2006
By 
FizzWiz (Pittsburgh, PA) - See all my reviews
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Overall, a good book. Could be a better even after excluding minor details- the ones noticed mentioned below.

Background necessary: Calculus- especially Taylor series, Integration by parts, solving for areas by integration and figuring out their limits; Even with a sufficient background, some proofs are quite rigorous or not well written enough, not sure which sometimes.

Comments based on first 7 Chapters of the book:
Standard deviation- excellently described
Relative frequency- NOT very well described. Makes sense on looking at chart in the book, but readers may forget to look at chart. A good definition for this important term is needed.
p. 43 They mention multinomial expansion before binomial distribution 1 chapter later. Very unnecessary, and doesn't make sense for the general reader to just stick it in there. It's like trying to squeeze information just to try to put something mathematically interesting that is more of a hinderance for learning permutations, combinations, and the multiplication rule. They show it to try to combine the principles together, but to make any sense of the multinomial expansion, besides choosing numbers to do it out, the proof to understand it fully is graduate level mathematics. A big no no for the book!! The least the book could do is expand by showing a specific example of this, and maybe even the proof itself, or just not mention it at all.

Section 2.7, p. 50 intro- too wordy. "relative frequencey of occurrence" in parentheses should probably be taken out for less confusion since a rel. freq. does not have to be based on a conditional probability occurring. Leaving it in leaves the reader at possible ambiguity.
Section 2.9, p. 62 Unnecessarily complicated- 1/5 * 3/4 = answer makes a lot more sense than them breaking it down into an unnecessary 7+ steps = answer.
Binomial Theorem probably could've been presented better. The idea of the binomial expansion and definition 3.7 (binomial distribution theorem) should be explained together right after definition 3.6 (explanation of a binomial experiment) rather than confusing the reader and leaving it off until later on.
p. 102-104 The book does a good job relating some word problems to the real world in good, brief explanations.
p.152 Step function should show hollow points if not the filled end points as well at least- too sloppy.
p. 172 Example 4.9 well done, but makes it sound like = (y- u)/o was intuitively obvious even to the beginner. The book tends to introduce some examples like this to introduce a theory. Just something one needs to get used to. It would be nice if they were able to put a sentence on page 1 about how some conecepts are inrtoduced by example first, but of course not everyone would read it anyway.
p. 188, sec. 4.8- great summary explaining existence for variety of statistical models
Example 5.1, p. 212- not a very good example. The table's correlation to the sample space given is overly ambiguous. Example is confusing, especially since they use the starting point starting from the top right corner instead of the top left corner and show no indication of what stands for what without reader figuring it out. Poorly set up.
p.213 typo- 6/9, not 8/9- tricky to figure out for a beginner
p.225 calculation- just add "= 1" to show solving of one of the integrals. Book sloppily leaves out this simple, but crucial step. A hard read for beginners to notice.
"degrees of freedom (d.f.)" can probably be better and simply defined than the book's "attempts," such as always one less than number of trials or something like that rather than always showing d.f. by notation only.

It's quite arguable if maybe just normal, or normal and t distributions and then central limit theorem should be mentioned in the book first, rather than throwing in all the different kinds of distributions in to learn for Chapter 3 first.
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Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
data present sufficient evidence, valid joint probability density function, power family distribution, yields the pth quantile, simultaneous confidence coefficient, independent samples experiment, attained significance level, show that the joint density, elementary experimental designs, estimated expected cell frequencies, appropriate rejection region, numerical descriptive measures, simulated sampling distribution, numerical events, factorization criterion, multinomial experiment, beta density functions, poorest applicants, additional tosses, balanced die, pivotal quantity, unbiased point estimators, pivotal method, hypergeometric probability distribution, conjugate gamma
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Thomson Learning, All Rights Reserved, New York, Applet Exercise Refer, Hypothesis Testing, Multivariate Probability Distributions, United States, The Analysis of Variance, Least Squares, Nonparametric Statistics, Mathematical Statistics, Use Theorem, Solution Let, Functions of Random Variables, Designing Experiments, Use Table, Upper Saddle River, Applet Exercise In Exercise, Next Trial, Solution In Example, Pearson Prentice Hall, Recall Exercise, Comparison of Beta Density Functions, Analysis of Categorical Data, Theory of Statistics
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