Update concerning COVID-19 – Distance Learning (home study) courses are still available. Find out more about distance learning at Pitman Training

Update concerning COVID-19 – Distance Learning (home study) courses are still available. Find out more about distance learning at Pitman Training

R Programming and Statistical Analysis

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 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.

Award and Associated Qualifications

Awarded 40 CPD points upon successful completion

Start Date

Flexible

Study Type

in centre, Online, or a combination

Training Type

course

Duration

40 hours

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    About this 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 understanding with the knowledge tests at the end of each section.

    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

    Aims and Objectives

    Pre-Requisites

    Finance Options

    Career Path

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      What's the difference?

      We offer a range of training packages in a range of subject areas and can offer blended learning opportunities to best meet your needs

      Course

      Our courses are practical in nature and focus on a single subject and can last anywhere from a few hours to a few days.

      Diploma

      Diplomas are designed to give you a complete skillset mapped to a specific career path and contain a number of core and elective courses