Course Code: rsttatan
Duration: 14 hours
Prerequisites:

There are no specific requirements needed to attend this course.

Overview:

Organization – Lab work and practical examples on real data

Course Outline:

Day One

  1. Introduction to R & Rstudio (2 hours)
    • Making R more friendly, R and available GUIs
    • Rstudio
    • Scripting in Rstudio
    • Navigation, sections and code folding
    • Troubleshooting and code debugging in RStudio
    • Related software and documentation
    • Getting help with functions and features
    • Projects in RStudio
    • Creating analytical reports with RStudio
    • Keyboard shortcuts and useful features
  2. Importing/Exporting data (1 hour)
    • Flat files – txt, csv
    • Spredsheet files – xls, xlsx
    • SPSS, SAS and other formats data
    • Accessing data from SQL data sources
    • SQL database connectivity and operations
  3. Organising data (2 hours)
    • Data types and classes
    • Data storage in R – Rdata format
    • Objects structure
    • Numbers and vectors
    • Matrix and table
    • Factors
    • Lists
    • Data Frames
    • Date and time
  4. Tabular representation (3 hours)
    • Overview of packages for data tables – dplyr, tidyr, data.table
    • Indexes and subscripts
    • Selecting, subsetting observations and variables
    • Filtering, grouping
    • Recoding transformations
    • Reshaping data
    • Merging data
    • Character manipulation, stringr package
    • Regular expressions

Day Two

  1. Related software and documentation (1 hour)
    • Rstudio and GIT - versioning
    • Markdown
    • Reports and presentations with LaTeX
    • Shiny web applications
  2. R and Statistics (2 hours)
    • Probability and Normal Distribution
    • Random numbers
    • Descriptive Statistics
    • Standarization and Normalization
    • Confidence Intervals
    • Hypothesis Testing
    • ANOVA
    • Qualitative data analysis
  3. Linear regression (2 hours)
    • Correlation coefficient and interpretation
    • Simple and multiple linear regression
    • Estimation methods – Least squares
    • Model validation – tests for violation of assumptions
    • Selecting variables – different approaches
    • Regulatizations – ridge and lasso regression
    • Generalized least square – nonlinearity
    • Logistic regression
  4. Graphical procedures (2 hours)
    • Basic plots for 1 variable
    • Visualizations for 2 and more variables
    • Graphical parameters
    • Special plots
    • Exporting plots to png, pdf and jpeg files
    • Extending graphical capabilities of R with ggplot2
  5. Help in R (1 hour)
    • Searching through documentation of R
    • R packages and documentation
    • R Cran Task View – search for problem solution
Sites Published:

United Arab Emirates - R for Statistical Analysis

Qatar - R for Statistical Analysis

Egypt - R for Statistical Analysis

Saudi Arabia - R for Statistical Analysis

South Africa - R for Statistical Analysis

Brasil - R for Statistical Analysis

Canada - R for Statistical Analysis

中国 - R for Statistical Analysis

香港 - R for Statistical Analysis

澳門 - R for Statistical Analysis

台灣 - R for Statistical Analysis

USA - R for Statistical Analysis

Österreich - R for Statistical Analysis

Schweiz - R for Statistical Analysis

Deutschland - R for Statistical Analysis

Czech Republic - R for Statistical Analysis

Denmark - R for Statistical Analysis

Estonia - R for Statistical Analysis

Finland - R for Statistical Analysis

Greece - R for Statistical Analysis

Magyarország - R for Statistical Analysis

Ireland - R for Statistical Analysis

Luxembourg - R for Statistical Analysis

Latvia - R for Statistical Analysis

España - R para el Análisis Estadístico

Italia - R for Statistical Analysis

Lithuania - R for Statistical Analysis

Nederland - R for Statistical Analysis

Norway - R for Statistical Analysis

Portugal - R for Statistical Analysis

România - R for Statistical Analysis

Sverige - R for Statistical Analysis

Türkiye - R for Statistical Analysis

Malta - R for Statistical Analysis

Belgique - R for Statistical Analysis

France - R for Statistical Analysis

日本 - R for Statistical Analysis

Australia - R for Statistical Analysis

Malaysia - R for Statistical Analysis

New Zealand - R for Statistical Analysis

Philippines - R for Statistical Analysis

Singapore - R for Statistical Analysis

Thailand - R for Statistical Analysis

Vietnam - R for Statistical Analysis

India - R for Statistical Analysis

Argentina - R para el Análisis Estadístico

Chile - R para el Análisis Estadístico

Costa Rica - R para el Análisis Estadístico

Ecuador - R para el Análisis Estadístico

Guatemala - R para el Análisis Estadístico

Colombia - R para el Análisis Estadístico

México - R para el Análisis Estadístico

Panama - R para el Análisis Estadístico

Peru - R para el Análisis Estadístico

Uruguay - R para el Análisis Estadístico

Venezuela - R para el Análisis Estadístico

Polska - R for Statistical Analysis

United Kingdom - R for Statistical Analysis

South Korea - R for Statistical Analysis

Pakistan - R for Statistical Analysis

Sri Lanka - R for Statistical Analysis

Bulgaria - R for Statistical Analysis

Bolivia - R para el Análisis Estadístico

Indonesia - R for Statistical Analysis

Kazakhstan - R for Statistical Analysis

Moldova - R for Statistical Analysis

Morocco - R for Statistical Analysis

Tunisia - R for Statistical Analysis

Kuwait - R for Statistical Analysis

Oman - R for Statistical Analysis

Slovakia - R for Statistical Analysis

Kenya - R for Statistical Analysis

Nigeria - R for Statistical Analysis

Botswana - R for Statistical Analysis

Slovenia - R for Statistical Analysis

Croatia - R for Statistical Analysis

Serbia - R for Statistical Analysis

Bhutan - R for Statistical Analysis

Nepal - R for Statistical Analysis

Uzbekistan - R for Statistical Analysis