Lithuanian Statistics Internship Project

This repository contains all the code and materials I developed during my internship at Lithuanian Statistics. The primary objective of my internship was to create a training platform for in-house training on R, as the organization transitioned from SAS to R. These resources are designed to help employees become proficient in R and include a series of tutorials developed using the LearnR package.

Table of Contents

• Introduction
• Project Overview
• Data
• Tutorial Structure
• Usage
• Dependencies
• Contributing
• License

Introduction

As Lithuanian Statistics moved from using SAS to R for data analysis, I was tasked with developing a comprehensive in-house training platform to facilitate this transition. The training materials are structured as interactive tutorials created using the LearnR package. These tutorials are designed to guide users through the fundamentals of R, focusing on the specific needs of the organization.

Project Overview

The repository is structured to support a smooth transition from SAS to R. The project includes:

• R Scripts: All the code developed during the internship.
• Interactive Tutorials: Four main parts that cover the essential aspects of R programming.
• Anonymized Data: Datasets in .xlsx format that have been anonymized for training purposes.

Data

The data used in these tutorials has been anonymized to protect sensitive information. The datasets are provided in Excel (.xlsx) format and are used throughout the tutorials to provide practical, hands-on experience with R.

Tutorial Structure

The training platform is divided into four main parts:

1. Introduction to R: Covers the basics of R, including installation, the RStudio environment, basic syntax, and data types.

2. Data Manipulation: Introduces key R packages like dplyr and tidyr for data wrangling, including filtering, transforming, and summarizing data.

3. Data Visualization: Focuses on creating visualizations using ggplot2, including scatter plots, bar charts, histograms, and more advanced plots.

4. Statistical Analysis: Guides users through basic statistical tests, regression analysis, and interpreting results in R.

Each tutorial is interactive, allowing users to write and execute R code within the platform, providing immediate feedback and reinforcing learning.

Usage

To use these materials:

1. Clone the repository to your local machine.
2. Install the necessary R packages (see Dependencies below).
3. Load the tutorials using the LearnR package, and follow along with the interactive instructions.
4. Explore the data using the provided .xlsx files.

These tutorials are designed to be self-paced, allowing users to progress at their own speed.

Dependencies

The tutorials and scripts in this repository require R and the following R packages:

• LearnR
• tidyverse
• readxl
• ggplot2
• dplyr
• tidyr

Install the required packages using:

install.packages(c("LearnR", "tidyverse", "readxl", "ggplot2", "dplyr", "tidyr"))