Here is a list of all modules:

[detail level 12345]

R Interface for Statistical Computing
Containers	The containers and generators the ROOT framework offers
Graphics	The graphics related classes
Graphics' Backends	Graphics' Backends interface classes
Cocoa backend	Interface to MacOS native graphics system
Win32 backend	Interface to Windows graphics
X11 backend	Interface to X11 graphics
2D Graphics	The 2D graphics related classes
libAfterImage interface	Classes interfacing to libAfterImage
FITS file	Interface to FITS file
Graphics pad	The TPad related classes
Basic graphics	The low level graphics classes
graphviz interface	Interface to the graphing package `graphviz`
Graphics file output	Interfaces to various file output formats
3D Graphics	The 3D graphics related classes
Event Display	The Event Display classes
Basic 3D graphics.	The basic 3D classes
OpenGL rendering	OpenGL rendering and utility classes
Histogram Library	A general description of the Histogram library is documented in the class TH1
Histograms and graphs painting classes.
Advanced spectra processing classes.
Input/Output Library	The library collecting the ROOT classes dedicated to data input and output
Math	The ROOT Mathematical Libraries
GenVector	Generic 2D, 3D and 4D vectors classes and their transformations (rotations)
MathCore	The Core Mathematical Library of ROOT. See the MathCore description page
Fitting and Parameter Estimation	Classes used for fitting (regression analysis) and estimation of parameter values given a data sample
Fit Method Classes	Classes describing Fit Method functions
Fit Data Classes	Classes for describing the input data for fitting
User Fitting classes	Main Classes used for fitting a given data set
Random Classes	Pseudo-random numbers generator classes and for generation of random number distributions
QuasiRandom number generators and distributions	Classes for generating QuasiRandom numbers and based on GSL
Function Classes and Interfaces	Interfaces (abstract classes) and Base classes used in MathCore and MathMore numerical methods for describing function classes
Generic Function Evaluation Interfaces	Interface classes for evaluation of function object classes in one or multi-dimensions
Internal Functor Classes	Internal classes for implementing Functor and Functor1D classes
Parameteric Function Evaluation Interfaces.	Interfaces classes for evaluation of parametric functions
Numerical Algorithms	Numerical Algorithm classes from the MathCore Library and MathMore Library libraries
One-dimensional Minimization	Classes for one-dimensional minimization
Numerical Integration	Classes for numerical integration of functions
Numerical Monte Carlo Integration Classes	Classes implementing method for Monte Carlo Integration
Multi-dimensional Minimization	Classes implementing algorithms for multi-dimensional minimization
Numerical Differentiation	Classes for numerical differentiation
One-dimensional Root-Finding	Classes implementing algorithms for finding the roots of a one-dimensional function
Function Approximation (ChebyshevApprox)	Numerical algorithm from the MathMore library and implemented using the GSL library
Multidimensional ROOT finding	Classes for finding the roots of a multi-dimensional system
Interpolation Classes	Classes for interpolation of points
Statistical functions	Probability density functions, cumulative distribution functions and their inverses (quantiles) for various statistical distributions (continuous and discrete)
Probability Density Functions (PDF)	Probability density functions of various statistical distributions (continuous and discrete)
Cumulative Distribution Functions (CDF)	Cumulative distribution functions of various distributions
Statistical functions from truncated distributions	Statistical functions for the truncated distributions
Quantile Functions	Inverse functions of the cumulative distribution functions and the inverse of the complement of the cumulative distribution functions for various distributions
Special functions	Special mathematical functions
MathMore	The Mathematical library providing some advanced functionality and based on GSL. See the MathMore Library page
Numerical Algorithms	Numerical Algorithm classes from the MathCore Library and MathMore Library libraries
One-dimensional Minimization	Classes for one-dimensional minimization
Numerical Integration	Classes for numerical integration of functions
Numerical Monte Carlo Integration Classes	Classes implementing method for Monte Carlo Integration
Multi-dimensional Minimization	Classes implementing algorithms for multi-dimensional minimization
Numerical Differentiation	Classes for numerical differentiation
One-dimensional Root-Finding	Classes implementing algorithms for finding the roots of a one-dimensional function
Function Approximation (ChebyshevApprox)	Numerical algorithm from the MathMore library and implemented using the GSL library
Multidimensional ROOT finding	Classes for finding the roots of a multi-dimensional system
Interpolation Classes	Classes for interpolation of points
Statistical functions	Probability density functions, cumulative distribution functions and their inverses (quantiles) for various statistical distributions (continuous and discrete)
Probability Density Functions (PDF)	Probability density functions of various statistical distributions (continuous and discrete)
Cumulative Distribution Functions (CDF)	Cumulative distribution functions of various distributions
Statistical functions from truncated distributions	Statistical functions for the truncated distributions
Quantile Functions	Inverse functions of the cumulative distribution functions and the inverse of the complement of the cumulative distribution functions for various distributions
Special functions	Special mathematical functions
QuasiRandom number generators and distributions	Classes for generating QuasiRandom numbers and based on GSL
TMinuit	The Minuit Minimization package
Minuit2 Minimization Library	New Object-oriented implementation of the MINUIT minimization package
SMatrix	SMatrix Package for high performance vector and matrix computations
Expression Template Classes
Generic Template Functions	These functions apply for any type T, such as a scalar, a vector or a matrix
Vector Template Functions	These functions apply to SVector types (and also to Vector expressions) and can return a vector expression or a scalar, like in the Dot product, or a matrix, like in the Tensor product
Matrix Template Functions	These function apply to matrices (and also Matrix expression) and can return a matrix expression of a particular defined type, like in the matrix multiplication or a vector, like in the matrix-vector product or a scalar like in the Similarity vector-matrix product
SMatrix Storage Representation
Matrix and Vector classes	Classes representing Matrices and Vectors of arbitrary type and dimension
Unuran
Monte Carlo	The Monte Carlo related packages
EG	Particle Data Group interface
Pythia6	The Pythia6 interface
Pythia8	The Pythia8 interface
VMC	Virtual Monte Carlo
PROOF	Classes defining the Parallel ROOT Facility, PROOF, a framework for parallel analysis of ROOT TTrees
PROOF kernel Libraries	The PROOF kernel libraries (libProof, libProofPlayer, libProofDraw) contain the classes defining the kernel of the PROOF facility, i.e
PROOF benchmark utilities	Set of utilities to benchmark a PROOF facility
XProofD client Library	The XProofD client library, libProofx, contain the classes providing the client to interact with the XRootD-based xproofd daemon
RooFit	RooFit toolkit classes. For documentation see (The RooFit Toolkit for Data Modeling)[http://root.cern.ch/drupal/content/roofit]
RooFitCore	Core RooFit classes
RooStats	RooStats is a package containing statistical tools built on top of RooFit
Tree Library	To store large quantities of same-class objects, ROOT provides the TTree and TNtuple classes
Tutorials	A collection of macros illustrating many aspect of ROOT
Containers tutorials	Examples showing the "containers' classes" usage.
Event display tutorials	Examples showing the "Event display classes" usage.
Graphics tutorials	Various examples showing the basic ROOT graphics
Graphs tutorials	Examples showing the "graphs classes" usage.
GUI tutorials	Example code which illustrates how to use the ROOT GUI
Histograms tutorials	Examples showing the "histograms' classes" usage.
Image tutorials	Examples showing the TImage class usage
IO tutorials	These tutorials illustrate some of the capabilities of the ROOT IO subsystem
Math tutorials	Examples showing the Math classes
TUnfold tutorials	Test programs for the classes TUnfold and related
TUnfoldDensity and TUnfoldBinning test suite	This is an example of unfolding a two-dimensional distribution
Multicore tutorials	These examples aim to illustrate the multicore features of ROOT, such as thread awareness and safety, multithreading and multiprocessing
Proof tutorials	These examples aim to illustrate the usage of PROOF
ProcFileElements	Class to hold information about the processed elements of a file
ProofAux	Selector used for auxiliary actions in the PROOF tutorials
ProofEvent	Selector for generic processing with Event
ProofEventProc	Selector to process trees containing Event structures
ProofFriends	Selector to process tree friends
ProofNtuple	Selector to fill a simple ntuple
ProofPythia	Selector to generate Monte Carlo events with Pythia8
ProofSimple	Selector to fill a set of histograms
ProofSimpleFile	Selector to fill a set of histograms and merging via file
ProofStdVec	Selector for generic processing with stdlib collections
ProofTests	Auxilliary selector used to test PROOF functionality
PyRoot tutorials	Examples showing how to write python script for Root
Pythia tutorials	Examples showing the pythia usage
RooFit Tutorials	These tutorials illustrate the main features of RooFit. Thir names are related to the aspect which is treated in the code
Spectrum tutorials	Examples showing the TSpectrum and TSpectrumPainter usage
Tree tutorials	Example code which illustrates how to use ROOT trees and ntuples