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R Intermediate

  • Length 1 day
  • Price  $745 inc GST
Course overview
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Why study this course

R is an open source and free programming language that was developed for statistical analysis and graphical data representation. It is commonly used by statisticians and academics internationally, as it is relatively easy to get up and running once you know the basics, even without a background in programming. The active user community behind R has contributed over 15,000 packages that extend the base functionality of R, making it easy to implement a vast range of techniques for data manipulation, analysis, and visualisation.

Building on the core concepts introduced in our R Beginner course, this Intermediate course focuses on practical skills in data manipulation, exploratory data analysis, customised data visualisations, and basic modelling techniques.

Guided by an experienced data analyst, you’ll work through hands-on exercises to strengthen your R coding skills and apply a range of functions to real-world datasets.

Nexacu Public Schedule

Nexacu is part of the Lumify Group, offering you the largest public schedule of end user applications and professional development training in Australia, New Zealand, and the Philippines. You can now access the schedule of courses and book, by clicking on the button below.

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What you’ll learn

After completing this course, students will be able to:

  • Create and manipulate objects in R

  • Use functions to perform and streamline data tasks

  • Work with relational data

  • Perform basic exploratory data analysis

  • Create customised visualisations

  • Apply basic modelling and prediction techniques

  • Identify and use functions suited to specific tasks


R Programming logo PNG

R Programming at Lumify Work

Learn R programming to analyse, manipulate, and visualise data more effectively.

Nexacu, part of the Lumify Group, delivers our R Programming data analysis training courses.


Who is the course for?

This course will suit professionals interested in diving deeper into data analysis and making data-driven decisions.


Course subjects

Introduction

  • Review of R data types and structures

  • Review of common syntax for accessing data in data frames

Importing Data

  • Importing data in RStudio

  • Packages and functions to import data into R

  • Using code to import data

  • Importing data from text files (csv)

  • Importing data from Excel

Workflow in R

  • Creating reusable scripts

Manipulating Data

  • The "tidyverse"

  • Summarising data

  • Ordering data

  • Working with dates

  • Converting character to date

  • Extracting years, months, days, or days of the week from dates

  • Adding columns to a data frame

  • Working with strings

  • Selecting and reordering columns in a data frame

  • Selecting rows based on values

  • Grouping data

  • Summarising data

  • Identifying blank values and non-number numbers

  • Working with data that contains missing values and non-number numbers

  • Removing missing values from a data set

  • Replacing values

  • Concatenating strings

  • Bin continuous variables into categories

Working with Relational Data

  • Adding new variables to a data frame from another

  • Mutating joins and merge()

  • Filtering joins

  • Exporting data to a file

Basic Exploratory Data Analysis

  • Choosing the right chart for your goal

  • Choosing the right chart for your data

  • Univariate analysis of numeric variables

  • Univariate analysis of categorical variables

  • Multivariate analysis of numeric variables

  • Multivariate analysis of numeric and categorical variables

  • Multivariate analysis of categorical variables

Univariate Analysis

  • Exploring the data distribution

  • Central tendency

  • Spread

  • Outliers

  • Shape of the distribution

Visual Representation of Distributions

  • Histograms

  • Boxplots

  • Dot charts / dot plots

  • Stem and leaf plots

  • Bar and column charts

Multivariate Analysis

  • Scatterplots and scatterplot matrix

  • Correlations

  • Bar and column charts

  • Line charts

  • Customising charts in R

  • Other graphics options

Basic Modelling

  • Modelling for prediction

  • Creating a linear model

  • How good is the model?

  • Assumptions

  • Making predictions from the model


Prerequisites

You should have completed our R Beginner course and be familiar with basic R syntax, data types, subsetting data, and using contributed packages.

Basic experience with RStudio is also helpful.


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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Nexacu Public Schedule

Nexacu is part of the Lumify Group, offering you the largest public schedule of end user applications and professional development training in Australia, New Zealand, and the Philippines. You can now access the schedule of courses and book, by clicking on the button below.