Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) Review

Average Reviews:

(More customer reviews)Are you looking to buy Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)? Here is the right place to find the great deals. we can offer discounts of up to 90% on Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics). Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) ReviewFor those who wants to understand what programns like spss, statistica and minitab do. Its not trivial but for the midle level student its very usefull. All the examples are in fortram language what is bad for me... But in general Monahan writes in very clear way, special thing in this kind of book.Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) OverviewThis book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis.For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians.The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression.The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. The book concludes with an examination of sorting, FFT and the application of other "fast" algorithms to statistics.Each chapter contains exercises that range in difficulty as well as examples of the methods at work.Most of the examples are accompanied by demonstration code available from the author's home page.

Want to learn more information about Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...

Data Manipulation with R (Use R) Review

Average Reviews:

(More customer reviews)Are you looking to buy Data Manipulation with R (Use R)? Here is the right place to find the great deals. we can offer discounts of up to 90% on Data Manipulation with R (Use R). Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

Data Manipulation with R (Use R) ReviewThis book along with Jim Albert's should be read by every statistician that does a lot of statistical computing. Both books help you learn R quickly and apply it to many important problems in research both applied and theoretical. Albert emphasizes applications in Bayesian statistics whereas Spector is teaching how to do data manipulation, things like merging and transposing data sets. These techniques can be easy to do in a language like SAS after a little training but in other programming languages it can be very difficult.Data Manipulation with R (Use R) OverviewThis book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data.In addition to the built-in functions, a number of readily available packages from CRAN (the Comprehensive R Archive Network) are also covered. All of the methods presented take advantage of the core features of R: vectorization, efficient use of subscripting, and the proper use of the varied functions in R that are provided for common data management tasks. Most experienced R users discover that, especially when working with large data sets, it may be helpful to use other programs, notably databases, in conjunction with R. Accordingly, the use of databases in R is covered in detail, along with methods for extracting data from spreadsheets and datasets created by other programs. Character manipulation, while sometimes overlooked within R, is also covered in detail, allowing problems that are traditionally solved by scripting languages to be carried out entirely within R. For users with experience in other languages, guidelines for the effective use of programming constructs like loops are provided. Since many statistical modeling and graphics functions need their data presented in a data frame, techniques for converting the output of commonly used functions to data frames are provided throughout the book.

Want to learn more information about Data Manipulation with R (Use R)?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...