SAS and R Data Management Statistical Analysis and Graphics 2nd Edition by Ken Kleinman, Nicholas Horton ISBN 1466584505 9781466584501

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Product details:

ISBN 10: 1466584505

ISBN 13: 978-1466584501

Author: Ken Kleinman, Nicholas J. Horton

SAS and R: Data Management, Statistical Analysis, and Graphics 2nd Edition: An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications.

New to the Second EditionThis edition now covers RStudio, a powerful and easy-to-use interface for R. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. It also includes extended examples of simulations and many new examples.

Enables Easy Mobility between the Two SystemsThrough the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book’s website.

 

SAS and R: Data Management, Statistical Analysis, and Graphics 2nd Edition Table of contents:

Data Input and Output

• Input
• Output

Data Management

• Structure and Meta-Data
• Derived Variables and Data Manipulation
• Merging, Combining, and Subsetting Datasets
• Date and Time Variables

Statistical and Mathematical Functions

• Probability Distributions and Random Number Generation
• Mathematical Functions
• Matrix Operations

Programming and Operating System Interface

• Control Flow, Programming, and Data Generation
• Functions and Macros
• Interactions with the Operating System

Common Statistical Procedures

• Summary Statistics
• Bivariate Statistics
• Contingency Tables
• Tests for Continuous Variables
• Analytic Power and Sample Size Calculations

Linear Regression and ANOVA

• Model Fitting
• Tests, Contrasts, and Linear Functions of Parameters
• Model Diagnostics
• Model Parameters and Results

Regression Generalizations and Modeling

• Generalized Linear Models
• Further Generalizations
• Robust Methods
• Models for Correlated Data
• Survival Analysis
• Multivariate Statistics and Discriminant Procedures
• Complex Survey Design
• Model Selection and Assessment

A Graphical Compendium

• Univariate Plots
• Univariate Plots by Grouping Variable
• Bivariate Plots
• Multivariate Plots
• Special Purpose Plots

Graphical Options and Configuration

• Adding Elements
• Options and Parameters
• Saving Graphs

Simulation

• Generating Data
• Simulation Applications

Special Topics

• Processing by Group
• Simulation-Based Power Calculations
• Reproducible Analysis and Output
• Advanced Statistical Methods

Case Studies

• Data Management and Related Tasks
• Read Variable Format Files
• Plotting Maps
• Data Scraping and Visualization
• Manipulating Bigger Datasets
• Constrained Optimization: The Knapsack Problem

 

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