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This module is a prerequisite to module 2, 3 and 4. So this module is strongly recommended to those participants who have poor skills on R software, or to test or review your skills on R Statistical Software.

Module Outline
  • Statistics with open source R
  • RSTudio
  • Introduction to Data Import
  • Introduction to Time Series with R
  • Conditional statements, Loops and Function creation
  • Introduction to analysis of gridded datasets

 


The trainer of this module is Edmondo Di Giuseppe 
Institute of Biometeorology, CNR-National Research Council Rome, Italy


This module is an elearning course, trainees are asked to pass quizzes and to upload the results of some exercises.

  • Introduction 

    0/1
    • About this Module
  • Statistics with OpenSource R 

    0/12
    • Introduction to Open Source R
    • R Install and set-up
    • R Package
    • The Kernel of R language (in a nutshell)
    • The Kernel of R language: Practising
    • Inline Help
    • The kernel of R language: Manipulation of Objects
    • The kernel of R language: Visualizing
    • The kernel of R language…. and now YOU MOVE! (An Example)
    • The kernel of R language: Matrix
    • The kernel of R language: data.frame
    • The kernel of R language: script file
  • R Studio 

    0/6
    • Lessons Outline
    • What is RStudio?
    • RSTUDIO: Download and install
    • RStudio Environment
    • Testing RSTUDIO
    • How to create a project
  • Data Import 

    0/13
    • Lessons Outline
    • Data Import
    • Data Import: Excel
    • How to import data from a .txt file
    • What kind of object dataRR is?
    • Writing commands on R script file
    • Exploration Data Analysis – Part 1
    • Calculate the missing data
    • Exploration Data Analysis – Part 2
    • Exploration Data Analysis – Part 3
    • Calculate cumulated precipitation
    • Exploration Data Analysis – Part 4
    • Calculate Spring cumulated precipitation
  • Time Series 

    0/10
    • Lessons Plan
    • R to analyse time series data
    • mon.cum.V and mon.cum.ts
    • Plotting and sub-setting a time series
    • Saving a plot
    • Finding Outliers
    • Replacing Outliers
    • Seasonal Decomposition
    • What we have learnt
    • Time Series Final Exercise
  • Conditional statements, Loops and Function creation 

    0/5
    • Lessons Plan
    • Saving and loading objects in R files
    • Conditional Statements: Part 1
    • exercise
    • Quiz
  • Introduction to analysis of gridded datasets 

    0/15
    • R overview
    • Raster Package
    • Import a NetCDF data file
    • Plotting a RasterBrick object
    • Quiz: months of cumulated precipitation plotted
    • Spatial and Time selection
    • Statistics across layers: Exercise
    • Quiz: Variables Mapped
    • Statistics across cells (horizontally)
    • Statistics across layers & cells – Exercise 1
    • Basic Raster Arithmetic: Part 1
    • Quiz: Vector
    • Basic Raster Arithmetic: Part 2
    • Quiz: describing dimensions dataRRg.yearly.7100 object
    • Basic Raster Arithmetic: Part 3
  • Links 

    0/1
    • Useful links
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