- Introduction to R.
- Understanding R Data Structures.
- Importing File.
- Manupulating Data.
R is language and enviromnent for statistical computing and graphics. It is a GNU project which is
similar to the S language and environment which was developed at Bell Laboratories by John
Chambers and collegues. R can be considered as a different implementation of S. There are
important differences, but much code written for S runs unaltered under R. R provides a wide variety
of statistical (linear and non linear modelling, classical statical tests, time-series analysis, classification,
clustering) and graphical techniques, and is highly extensible.
- R Language training is aimed both for individuals starting with programming and people who
already have other programming language skills..
- What is R?
- Why R?
- Installing R.
- R environment.
- How to get help in R.
- R console and Editor.
- Variables in R.
- Scalars.
- Vectors.
- Matrices.
- List.
- Data frames.
- Using c, Cbind, Rbind, attach and detach functions in R.
- Factors.
- Reading Tabular Data files.
- Reading CSV files
- Importing data from excel.
- Importing data from SAS.
- Accessing database.
- Saving in R data.
- Loading R data objects.
- Writing to files.
- Selecting rows/observations.
- Selecting columns/fields.
- Merging data.
- Relabeling the column names.
- Converting variable types.
- Data sorting.
- Data aggregation.
- Commonly used Mathematical Functions.
- Commonly used Summary Functions.
- Commonly used String Functions.
- User-defined functions.
- Local and global variable.
- While loop.
- If loop.
- For loop.
- Arithmetic operations.
- Box plot.
- Histogram.
- Pareto charts.
- Pie graph.
- Line chart.
- Scatterplot.