### Basic Data Types and Data Structures (Introduction to Statistical Computing)

Introduction to the course: statistical programming for autonomy, honesty,
and clarity of thought. The functional programming idea: write code by
building functions to transform input data into desired outputs. Basic data
types: Booleans, integers, characters, floating-point numbers. Subtleties of
floating point numbers. Operators as basic functions. Variables and names.
An example with resource allocation. Related pieces of data are bundled into
larger objects called data structures. Most basic data structures: vectors.
Some vector manipulations. Functions of vectors. Naming of vectors.
Continuing the resource-allocation example. Building more complicated data
structures on top of vectors. Arrays as a first vector structure. Matrices as a special type of array; functions for matrix arithmetic and
algebra: multiplication, transpose, determinant, inversion, solving linear
systems. Using names to make calculations clearer and safer:
resource-allocation mini-example. Lists for combining multiple types of
values; access sub-lists, individual elements; ways of adding and removing
parts of lists. Lists as key-value pairs. Data frames: the data structure for
classic tabular data, one column per variable, one row per unit; data frames as
hybrids of matrices and lists. Structures of structures: using lists
recursively to creating complicated objects; example with `eigen`.

Slides

Introduction to Statistical Computing

Posted at September 04, 2013 01:40 | permanent link