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Szkolenie Introduction to R

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Czas trwania

24 godzin(y) (po 8h lekcyjnych dziennie)
 

W cenie szkolenia:

  • efektywne szkolenie w małej grupie - średnio 4 osoby
  • materiały szkoleniowe (przygotowane przez wykładowcę)
  • książka powiązana tematycznie ze szkoleniem lub materiały drukowane
  • certyfikaty w języku polskim i angielskim, e-certyfikat
  • obiad
  • catering (napoje i słodycze)
 

Terminy Szkoleń Otwartych

Data rozpoczęcia Miejscowość Cena netto kursu
2012-05-29 Wrocław od 2460 do 2890 PLN - zapisz się!
2012-05-29 Poznań od 2460 do 2890 PLN - zapisz się!
2012-06-04 Gliwice od 2460 do 2890 PLN - zapisz się!
2012-06-11 Kraków od 2460 do 2890 PLN - zapisz się!
2012-06-18 Łódź od 2460 do 2890 PLN - zapisz się!
2012-06-19 Warszawa od 2460 do 2890 PLN - zapisz się!
2012-06-25 Opole od 2460 do 2890 PLN - zapisz się!
2012-06-25 Częstochowa od 2460 do 2890 PLN - zapisz się!
2012-06-26 Warszawa od 2460 do 2890 PLN - zapisz się!
2012-07-09 Gliwice od 2460 do 2890 PLN - zapisz się!

Więcej Terminów! >>

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Node ID: 20299

Charakterystyka kursu

Forecasters, statisticians, managers, analysts who want to use R software http://www.r-project.org/.

It shows how use the software in available GUI's and command line.

 

 

Zagadnienia omawiane na kursie

  • Introduction and preliminaries
    • Making R more friendly, R and available GUIs
    • The R environment
    • Related software and documentation
    • R and statistics
    • 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 specific 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 builtin 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

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