Intermediate “R” Interest?

Gauging interest on a possible “Intermediate R” course. Send and email to office@cmiae.org if you might be interested in taking this course, or to let us know what stats courses you are interested in for 2019!
Course description from the instructor, Carl Schwarz:
Intermediate R
Description:
This is not a course in statistics, but rather in using R to solve more advanced problems that go beyond simple statistical analyses. For example, how do I deal with date and time data? Suppose you have 5 years of data and with the same analysis to be done for each year’s data. What is the best way to structure this in R? How do I write a function to do a yearly analysis that is beyond what is commonly available in R?  How do I restructure my data so do a similar analysis on 10 separate variables?  How do I plot my spatial data on a map? How do I manipulate shape-files? How do I make an interactive graphic (visualization)?
Many users of R quickly outgrow simply uses of R and need to deal with more complicated data manipulation and analyses.
This course builds on the introduction to R with the following topics:
– dealing with date and time data
– reshaping data from wide to long formats (primarily using the reshape2 package)
– beyond the data frame – the list structure
– split-apply-combine – sub-group analyses (primarily using the plyr package)
– packaging code into functions
– advanced ggplot (faceting, dealing with maps)
– introduction to data visualization (using ggvis and shiny package)
– generating reports (markdown, Sweave)
– basic spatial data analysis (primarily using the sp data classes). Topics for basic spatial data analysis include:
  • basic plotting of points on a google maps/ open street maps
  • importing shape files; sp data structures (polygons, lines, points)
  • basic introduction into projections
  • plotting sp data structures including chorpleth/ bubble/  maps
  • basic operations union/ intersection/ masking/ membership/ closest feature
  • simple regression using spatial data
  • simple logistic regression using spatial data
Prerequisties
Basic knowledge of R/Rstudio.

Contact

  • Phone 250-837-9311
  • Fax 250-837-9311
  • Email

Mailing Address

  • P.O. Box 2568
  • Revelstoke, British Columbia V0E 2S0
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