TRB2 REGION, Statistical Methods with R Programming- DAKA

Project Title 15

TRB2 REGION, Statistical Methods with R Programming- DAKA

Name of

legal entity

Country

Name of client

Origin of funding

Dates 

(start-end)

Name of consortium 

members, if any

BYS Grup

Türkiye

Eastern Anatolia Development Agency (DAKA)

National (Republic of Türkiye)

November 2018

BYS Grup

Detailed description of project

Type and scope of services provided

R Programming is a powerful and versatile programming language and environment used primarily for statistical computing and graphics. It's widely used among statisticians and data analysts for data mining, data analysis, and graphical representation of data. R offers an extensive package ecosystem and is highly extensible, allowing for a wide range of statistical techniques including linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, and more. It's known for its capability to produce well-designed publication-quality plots.

As a service, R Programming training has been organised and conducted for the Eastern Anatolia Development Agency. The training program was designed to provide comprehensive instruction in R programming, covering fundamental concepts, tools, and applications. Participants gained practical skills and theoretical understanding necessary to apply R in various data analysis and statistical contexts.

The training program was designed to be interactive and practical, ensuring participants not only understood the theoretical aspects of R programming but also gained hands-on experience in applying these concepts to real-world data analysis scenarios.

R programming training was about:

  • Introduction to the R interface and environment setup.
  • Navigating and customizing the RStudio interface for efficient workflow.
  • Practical exercises on variable assignments and data storage.
  • Exploring various comparison operators in R.
  • Understanding assignment operators and their use in R.
  • Comprehensive overview of data structures like vectors, matrices, lists, and data frames.
  • Introduction to basic data types (numeric, character, logical, etc.).
  • Writing custom functions in R for specific tasks.
  • Managing date and time data in R.
  • Apply functions in R.
  • Techniques for reading from and writing to various file formats (CSV, Excel, etc.).