Basic Business Statistics or R Programming for Bioinformatics

Basic Business Statistics: Concepts and Applications

Author: Mark L Berenson

Berenson shows students how statistics is use in each functional area of business. This edition features statistics in real-business scenarios, web cases, data analysis and interpretation of software results, case studies and team projects, as well as visual explorations of statistical concepts. This book is intended for undergraduate and graduate students taking courses in statistics. 

Booknews

Using case studies and chapter review problems, the authors attempt to make statistics and its business applications with Microsoft Excel software as painless as possible. After making the case for what's in it for productivity and quality-minded managers, they ease into Excel functions for analyzing and presenting data, hypothesis testing, regression, and time-series analysis. Appends a math and algebra review, summation notation, standard statistical tables and symbols, special data sets for team projects, and documentation for the CD-ROM files. Indexed by book subjects and Microsoft Excel features. The CD-ROM includes the PHStat statistics add-in for Excel for use in business statistics courses. Annotation c. by Book News, Inc., Portland, Or.

Interesting book: Vision of the Anointed or Worlds at War

R Programming for Bioinformatics

Author: Robert Gentleman

The Bioconductor project was initiated in 2001 to provide a resource of R packages that specifically address bioinformatics problems. Written by the leader of this project and the original developer of the R software, Bioinformatics with R provides an overview of techniques to develop R programming skills for bioinformatics. The book presents comprehensive coverage of a broad range of key topics, including R language fundamentals, object-oriented programming in R, foreign language interfaces, building R packages, handling different data technologies, and debugging. It includes a number of detailed illustrative bioinformatics examples as well as exercises to demonstrate techniques.

Table of Contents:

1 Introducing R 1

2 R Language Fundamentals 5

3 Object-Oriented Programming in R 67

4 Input and Output in R 119

5 Working with Character Data 145

6 Foreign Language Interfaces 183

7 R Packages 211

8 Data Technologies 229

9 Debugging and Profiling 273

References 301

Index 305