R Programming and Statistical Analysis

About the Course

The course includes a series of video lectures combined with a variety of conceptual and hands-on activities to help you develop skills in manipulating and analysing data, interpreting results, and visualising your data effectively. R is widely recognised as a powerful programming language and environment for data manipulation, statistical computing, and graphical display. R provides a variety of tools and techniques and is easily extensible. It’s an open-source programming language and a vital tool for data wrangling and
analysis.

R also includes a robust data handling and storage facility, as well as an extensive, integrated collection of tools for data analysis and graphical display. You’ll explore all of this and more as you work through the three modules of the course and test your under-standing with the knowledge tests at the end of each section.

R Programming and Statistical Analysis

Your details

Training Centre

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Course Info

Duration 40 hours. This will vary based on prior knowledge and ability.
Training Type Course
Study Type In centre, Online

Awards & Qualifications

Awarded 40 CPD points upon successful completion

Is this course right for me?

In this course, you’ll learn the fundamental tools and packages to manipulate, organise, analyse, and visualise data using the R programming language in the RStudio developer environment.

Is this course for you?

This course is for those who are interested in learning the R programming language for the purposes of data manipulation, statistical computing, and graphical display of data.

Awarded 40 CPD points upon successful completion
Duration 40 hours. This will vary based on prior knowledge and ability.

Course Content

Course Content

Module 1: R Programming for Beginners Getting Started with R; Exploring R Vectors; Leveraging R with Matrices, Arrays, and Lists;
Understanding Data Frames, Factors, and Strings
Module 2: Datasets in R Loading and Saving Data; Transforming Data; Selecting, Filtering, Ordering, and Grouping Data;
Joining and Visualising Data
Module 3: Statistical Analysis and Modelling in R Working with Probability Distributions; Understanding and Interpreting Statistical Tests; Statistical Analysis on Your Data; Performing Regression Analysis

Course Overview

Aims and Objectives

The aim of the course is for you to develop a strong foundation in the R programming language that you can put to effective use in the field of data analysis.

Career Path

To become an effective data analyst, you’ll need several programming languages in your toolkit. R is among the most sought-after skills among data analysts.

Pre-Requisites

Strong critical-thinking and problem-solving skills, a strong background in mathematics (e.g., advanced algebra), and some experience with coding.

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