R Programming

R Programming Training Outline

Overview
  • History of R
  • Advantages and disadvantages
  • Downloading and installing
  • How to find documentation

    Introduction
  • Using the R console
  • Getting help
  • Learning about the environment
  • Writing and executing scripts
  • Object oriented programming
  • Introduction to vectorized calculations
  • Introduction to data frames
  • Installing packages
  • Working directory
  • Saving your work
    Variable types and data structures
  • Variables and assignment
  • Data types
  • Numeric, character, boolean, and factors
  • Data structures
  • Vectors, matrices, arrays, dataframes, lists
  • Indexing, subsetting
  • Assigning new values
  • Viewing data and summaries
  • Naming conventions
  • Objects
    Getting data into the R environment
  • Built-in data
  • Reading data from structured text files
  • Reading data using ODBC
    Dataframe manipulation with dplyr
  • Renaming columns
  • Adding new columns
  • Binning data (continuous to categorical)
  • Combining categorical values
  • Transforming variables
  • Handling missing data
  • Long to wide and back
  • Merging datasets together
  • Stacking datasets together (concatenation)
    Handling dates in R
  • Date and date-time classes in R
  • Formatting dates for modeling
    Control flow
  • Truth testing
  • Branching
  • Looping
    Functions in depth
  • Parameters
  • Return values
  • Variable scope
  • Exception handling

    Functions in depth
  • Parameters
  • Return values
  • Variable scope
  • Exception handling
    Applying functions across dimensions
  • Sapply, lapply, apply
    Exploratory data analysis (descriptive statistics)
  • Continuous data
  • Distributions
  • Quantiles, mean
  • Bi-modal distributions
  • Histograms, box-plots
  • Categorical data
  • Tables
  • Barplots
  • Group by calculations with dplyr
  • Split-apply-combine
  • Melting and casting data
    Inferential statistics
  • Bivariate correlation
  • T-test and non-parametric equivalents
  • Chi-squared test

  • Inferential statistics
  • Bivariate correlation
  • T-test and non-parametric equivalents
  • Chi-squared test
    Base graphics
  • Base graphics system in R
  • Scatterplots, histograms, barcharts, box and whiskers, dotplots
  • Labels, legends, titles, axes
  • Exporting graphics to different formats
    Advanced R graphics: ggplot2
  • Understanding the grammar of graphics
  • Quick plots (qplot function)
  • Building graphics by pieces (ggplot function)

    General linear regression
  • Linear and logistic models
  • Regression plots
  • Confounding / interaction in regression
  • Scoring new data from models (prediction)

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About BitraNet Inc

Bitranet Inc is a fast growing US based IT Software development & Staff augmentation firm, We also have development centers in Schaumburg (Chicago), IL and Hyderabad, India. Bitranet established in 1996