Technologies / Data & Analytics

R in data analysis and research

The training introduces participants to the world of data analysis using the R language, focusing on its applications in scientific research. The program combines statistical theory with practical use of analytical tools available in R. Through hands-on workshops, participants learn to process data, perform statistical analysis and visualize results in a clear and professional manner.

Issues

Fundamentals of programming in R
Importing and exporting data
Data manipulation and transformation
Descriptive statistics and exploratory data analysis
Parametric and non-parametric tests
Analysis of variance (ANOVA)
Linear and logistic regression models
Data visualization with the ggplot2 package
Generation of statistical reports
Multivariate analysis
Dimensionality reduction methods
Integration of R with other research tools

Benefits

Practical ability to load and prepare data for analysis in the R environment.
Efficiently perform basic and advanced statistical analysis on a variety of data sets.
Create professional and clear visualizations of research results.
Ability to automate repetitive analytical procedures through R scripts.
Knowledge of the most important packages that extend the analytical capabilities of the R language.
Ability to interpret the results of statistical analysis and draw research conclusions.
Ability to select appropriate analytical methods for different types of research problems.

Who is this training for?

Scientists and academic researchers

Data analysts at research institutions

Research and development specialists

PhD students and researchers

Statisticians and mathematicians

Engineers working with data

Employees of analytical departments

Market research specialists

Prerequisites

Basic knowledge of descriptive statistics and statistical inference
Experience in working with tabular data
Knowledge of basic concepts related to data analysis
Ability to think logically and solve analytical problems
General knowledge of the research process and scientific methods

Training program

Syntax basics

Analysis packages
Statistical analysis
Descriptive statistics

Analysis of variance
Regression and correlation
Data visualization

Advanced visualizations
Interactive charts
Publication of results

Time series analysis
Predictive modeling
Data dimensionality reduction
Nonparametric methods

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For R in data analysis and research we recommend: Basic knowledge of descriptive statistics and statistical inference; Experience in working with tabular data; Knowledge of basic concepts related to data analysis.

What is the format and duration of this training?

The training lasts 1 day and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Scientists and academic researchers; Data analysts at research institutions; Research and development specialists.