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R Programming for Data Analysis - Intermediate

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

R is a programming language specifically developed for the statistical analysis of data and for producing graphical output. We introduced the core elements of R programming in our beginner course. This intermediate course is the second in our R series and focuses on:

  • data manipulation

  • basic exploratory data analysis

  • creating customised data visualisations

  • basic modelling 

Our experienced Data Analyst will guide you through exercises to practice writing R code, use a variety of different functions, produce graphical output, and view the results.

Nexacu Public Schedule

With Lumify Group's acquisition of Nexacu, we're pleased to now offer you the largest public schedule of end user applications training in Australia and New Zealand. As we move to consolidate our End User offering with Nexacu, as an interim measure you can now access the schedule of the most closely aligned courses and book, by clicking on the link below.

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What you’ll learn

After completing this course, students will be able to:

  • Perform basic exploratory data analysis

  • Conduct basic modelling and prediction

  • Find functions to perform specific tasks

  • Create and manipulate objects

  • Work with relational data


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R Programming at Lumify Work

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


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

  • Convert character to date

  • Extract years from dates

  • Extract months from dates

  • Extract days from dates

  • Extract days of the week from dates

  • Add 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

  • Concatenate strings

  • Bin continuous variables into categories

Working with Relational Data

  • Add 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

  • Create a linear model

  • How good is the model?

  • Assumptions

  • Making predictions from the mode


Prerequisites

You should have attended our R Programming for Data Analysis - Beginner course and have a basic understanding of R syntax.

It is assumed that you are familiar with:

  • basic R syntax

  • data types and structures

  • know how to subset data

  • know how to install and use contributed packages and their functions

  • basic familiarity with working in RStudio is 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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