Course Code: nsorf
Duration: 28 hours
Prerequisites:

This training is targeted for the grades of statisticians and above. Participants may not have basic knowledge of programming.

Overview:

This bespoke course will provide an in-depth insight into how to analyze and visualize data in R and create reproducible data analysis reports and communicate statistical results correctly and effectively.

Objectives:

  • Knowledge of the syntax and basis of the R programming language;
  • An overview of the packages applicable for statistical production;
  • Descriptive statistics with R;
  • Data visualisation with R and programming.

At the end of the training course, participants should be able to develop:

  • Basic R code;
  • Perform analysis of large databases and complex surveys using R software.
Course Outline:

Day one:

  • Introduction to the R language funamentals

  • Overview of the RStudio application and REPL

  • R data structure essentials

  • Exploratory data analysis with ggplot2

  • Accessing data from packages like eurostat

Day two:

  • Reading data files (XML, JSON, CSV, XLSX) into R

  • Data cleaning and manipulation with the tidyverse

  • Summary statistics of numeric, categorical and hierarchical datasets

  • Designing print quality data visualisations with ggplot2

  • Building rich reports with RMarkdown in both PDF and HTML formats

Day three:

  • Working with GIS data in R

  • Creating utility functions for automating data analysis via user-defined functions

  • Designing static and interactive maps, including; geo scatter plots and choropleth

  • Working with time series data in R

  • Manipulating dates and datetimes in R

  • Producing static and interactive time series 

Day four:

  • Linear and non-linear regression

  • Summarising and comparing models using broom and modelr

  • Performing and evaluating statistical tests in R

  • Presenting model results in static and interactive tables