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Beginning R: An Introduction to Statistical Programming [Paperback]

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  • Category: Books (Business &Amp; Economics)
  • Author:  Pace, Larry
  • Author:  Pace, Larry
  • ISBN-10:  1430245549
  • ISBN-10:  1430245549
  • ISBN-13:  9781430245544
  • ISBN-13:  9781430245544
  • Publisher:  Apress
  • Publisher:  Apress
  • Pages:  336
  • Pages:  336
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Nov-2012
  • Pub Date:  01-Nov-2012
  • SKU:  1430245549-11-SPRI
  • SKU:  1430245549-11-SPRI
  • Item ID: 100164517
  • List Price: $39.99
  • Seller: ShopSpell
  • Ships in: 5 business days
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  • Delivery by: Dec 02 to Dec 04
  • Notes: Brand New Book. Order Now.

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics.

R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.

  • Covers the freely-available R language for statistics
  • Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more
  • Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done
Part I. Learning the R Language

1. Getting R and Getting Started

2. Programming in R

3. Writing Reusable Functions

4. Summary Statistics

Part II. Using R for Descriptive Statistics

5. Creating Tables and Graphs

6. Discrete Probability Distributions

7. Computing Standard Normal Probabilities

Part III. Using R for Inferential Statistics

8. Creating Confidence Intervals

9. Performing t Tests?

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