R Introductie

Word data-analist met de R-workshop: dé praktische start voor professionals die willen groeien in data science en analytics.

De workshop R is bedoeld voor professionals die geïnteresseerd zijn in de analytics binnen data science. Deze workshop sluit goed aan wanneer je de ambitie hebt om dataanalist (of daaraan gerelateerd) te worden.

Wil je verder in de data science en -analyse, dan is affiniteit vereist met wiskunde in het algemeen en met statistiek in het bijzonder. Onderdelen als kansverdelingen en binomiaalcoëfficiënten hebben geen geheimen voor je. Je hebt kennis van algebra op gebieden van matrixrekenen, coördinatentransformaties en de toepassingen daarvan. In individuele trajecten kan hier flexibel op geschakeld worden door ontbrekende kennisgebieden op te vangen met cursus(s/onderdel)en op maat.

• Introduction and preliminaries
  • The R environment
  • Related software and documentation
  • R and statistics
  • R and the window system
  • Using R interactively
  • An introductory session
  • Getting help with functions and features
  • R commands, case sensitivity, etc.
  • Recall and correction of previous commands
  • Executing commands from or diverting output to a file
  • Data permanency and removing objects

• Simple manipulations; numbers and vectors
  • Vectors and assignment
  • Vector arithmetic
  • Generating regular sequences
  • Logical vectors
  • Missing values
  • Character vectors
  • Index vectors; selecting and modifying subsets of a data set
  • Other types of objects

• Objects, their modes and attributes
  • Intrinsic attributes: mode and length
  • Changing the length of an object
  • Getting and setting attributes
  • The class of an object

• Ordered and unordered factors
  • A specifc example
  • The function tapply() and ragged arrays
  • Ordered factors

• Arrays and matrices
  • Arrays
  • Array indexing. Subsections of an array
  • Index matrices
  • The array() function
    • Mixed vector and array arithmetic. The recycling rule
  • The outer product of two arrays
  • Generalized transpose of an array
  • Matrix facilities
    • Matrix multiplication
    • Linear equations and inversion
    • Eigenvalues and eigenvectors
    • Singular value decomposition and determinants
    • Least squares fitting and the QR decomposition
  • Forming partitioned matrices, cbind() and rbind()
  • The concatenation function, c(), with arrays
  • Frequency tables from factors

• Lists and data frames
  • Lists
  • Constructing and modifying lists
    • Concatenating lists
  • Data frames
    • Making data frames
    • attach() and detach()
    • Working with data frames
    • Attaching arbitrary lists
    • Managing the search path

• Reading data from files
  • The read.table() function
  • The scan() function
  • Accessing built-in datasets
    • Loading data from other R packages
  • Editing data

• Probability distributions
  • R as a set of statistical tables
  • Examining the distribution of a set of data
  • One- and two-sample tests

• Grouping, loops and conditional execution
  • Grouped expressions
  • Control statements
    • Conditional execution: if statements
    • Repetitive execution: for loops, repeat and while

• Writing your own functions
  • Simple examples
  • Defining new binary operators
  • Named arguments and defaults
  • The '...' argument
  • Assignments within functions
  • More advanced examples
    • Efficiency factors in block designs
    • Dropping all names in a printed array
    • Recursive numerical integration
  • Scope
  • Customizing the environment
  • Classes, generic functions and object orientation

• Statistical models in R
  • Defining statistical models; formulae
    • Contrasts
  • Linear models
  • Generic functions for extracting model information
  • Analysis of variance and model comparison
    • ANOVA tables
  • Updating fitted models
  • Generalized linear models
    • Families
    • The glm() function
  • Nonlinear least squares and maximum likelihood models
    • Least squares
    • Maximum likelihood
  • Some non-standard models

• Graphical procedures
  • High-level plotting commands
    • The plot() function
    • Displaying multivariate data
    • Display graphics
    • Arguments to high-level plotting functions
  • Low-level plotting commands
    • Mathematical annotation
    • Hershey vector fonts
  • Interacting with graphics
  • Using graphics parameters
    • Permanent changes: The par() function
    • Temporary changes: Arguments to graphics functions
  • Graphics parameters list
    • Graphical elements
    • Axes and tick marks
    • Figure margins
    • Multiple figure environment
  • Device drivers
    • PostScript diagrams for typeset documents
    • Multiple graphics devices
  • Dynamic graphics

• Packages
  • Standard packages
  • Contributed packages and CRAN
  • Namespaces

• OS facilities
  • Files and directories
  • Filepaths
  • System commands
  • Compression and Archives

Op deze module is geen aparte certificering van toepassing.