R meet up slides.pptx

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These are slides from the second Alamo Area R user group meeting, where I gave an intro to R and RStudio

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R meet up slides.pptx

  1. 1. Introduc)on  to     R  and  RStudio   Corey  S.  Sparks   Department  of  Demography   The  University  of  Texas  at  San  Antonio   September  22,  2012  Sponsored  by  the  UTSA  Department  of  Demography  
  2. 2. What  is  R?  •  R  is  a  system  for  sta)s)cal  computa)on  and   graphics.    •  It  is  heavily  influenced  by  the  S  language  •  R  was  ini)ally  wriJen  by  Ross  Ihaka  and   Robert  Gentleman  at  the  Department  of   Sta)s)cs  of  the  University  of  Auckland  in   Auckland,  New  Zealand.  •  The  “R  Core  Team”  maintain  the  source  code   for  the  soPware  and  release  regular  updates  
  3. 3. What  is  R?  •  The  R  soPware  contains  func)onality  for  a   large  number  of  sta)s)cal  procedures.  •  Linear  and  generalized  linear  models  •  Nonlinear  regression  models  •  Time  series  analysis  •  Classical  parametric  and  nonparametric  tests,   clustering  and  smoothing.  
  4. 4. What  is  R?  •  In  addi)on,  the  R  project  is  added  to  by  many   of  its  users,  who  write  source  code  for  many   different  types  of  analy)cal  procedures  •  Everything  from  analy)cal  chemistry  to   epidemiology  to  linguis)cs     –  OPen  code  is  wriJen  in  FORTRAN  or  C++  and   ported  to  R   –  Currently  4,045  different  user-­‐wriJen  libraries   available  
  5. 5. Where  can  I  run  R?    •  R  runs  on  a  variety  of  plaorms   –  Windows   –  Mac  OS  X   –  Linux   –  Unix  •  32  and  64  bit  installa)ons  •  Support  for  parallel  compu)ng  and  clusters  
  6. 6. Revolu)on  R  •  Commercial  version  of  R  soPware  •  Revolu)on  R  is  compiled  for  mul)-­‐core   support  •  Allows  for  a  marked  reduc)on  in  computa)on   )mes  because  of  op)mized  code  and  certain   math  system  libraries  (BLAS,  ATLAS,  etc)  
  7. 7. What  makes  R  so  great?  •  Open  source  •  User  community  •  Cudng  edge  development  •  Integra)on  with  low  level  programming   languages  •  Flexibility  •  Mul)-­‐language  support  
  8. 8. The  R  Interface  •  Depends  on  where  you  run  it  •  Different  OS’s  have  very  different  interfaces  •  R  is  inherently  command  line-­‐oriented  •  Several  GUIs  have  been  wriJen  
  9. 9. RStudio  •  Rela)vely  recent  incarna)on  of  an  R  IDE  •  Open  source    •  Desktop  and  server  versions  •  Lots  of  cool  features   –  syntax  highligh)ng   –  workspace  and  data  browser/editor   –  integrated  help  system   –  integrated  history   –  runs  on  all  OS’s  
  10. 10. RStudio  Screen  
  11. 11. Code  editor  
  12. 12. R  command  console  
  13. 13. Workspace  browser  
  14. 14. Command  History  
  15. 15. Package  manager  
  16. 16. File  manager  
  17. 17. Plot  manager  
  18. 18. Integrated  help  system  
  19. 19. Addi)onal  Cool  things  •  Mul)ple  project  management   –  Keep  mul)ple  code  files  for  separate  projects  •  Lots  of  keyboard  shortcuts  •  Generate  HTML  reports  with  knitr  •  Customized  IDE  

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