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<!DOCTYPE html>
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<title>1 Introduction | Introduction to R for Crime Analysts</title>
<meta name="description" content="This course is designed to help you transition from SPSS to R, demonstrating that all of the functionality you’re accustomed to in SPSS can be replicated—and often enhanced—in R. By the end of this course, you will be equipped with the knowledge and skills to conduct your analyses in R, whether you’re dealing with basic descriptive statistics, survey data, or more advanced statistical models." />
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<meta property="og:title" content="1 Introduction | Introduction to R for Crime Analysts" />
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<meta property="og:description" content="This course is designed to help you transition from SPSS to R, demonstrating that all of the functionality you’re accustomed to in SPSS can be replicated—and often enhanced—in R. By the end of this course, you will be equipped with the knowledge and skills to conduct your analyses in R, whether you’re dealing with basic descriptive statistics, survey data, or more advanced statistical models." />
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<meta name="twitter:title" content="1 Introduction | Introduction to R for Crime Analysts" />
<meta name="twitter:description" content="This course is designed to help you transition from SPSS to R, demonstrating that all of the functionality you’re accustomed to in SPSS can be replicated—and often enhanced—in R. By the end of this course, you will be equipped with the knowledge and skills to conduct your analyses in R, whether you’re dealing with basic descriptive statistics, survey data, or more advanced statistical models." />
<meta name="author" content="Daniel Hammocks, Senior Data Scientist at Mayor’s Office for Policing and Crime" />
<meta name="date" content="2024-08-28" />
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<li class="chapter" data-level="" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i>Preface</a>
<ul>
<li class="chapter" data-level="" data-path="index.html"><a href="index.html#purpose-of-this-book"><i class="fa fa-check"></i>Purpose of this Book</a></li>
<li class="chapter" data-level="" data-path="index.html"><a href="index.html#about-the-author"><i class="fa fa-check"></i>About the Author</a></li>
</ul></li>
<li class="chapter" data-level="1" data-path="introduction.html"><a href="introduction.html"><i class="fa fa-check"></i><b>1</b> Introduction</a>
<ul>
<li class="chapter" data-level="1.1" data-path="introduction.html"><a href="introduction.html#overview"><i class="fa fa-check"></i><b>1.1</b> Overview</a></li>
<li class="chapter" data-level="1.2" data-path="introduction.html"><a href="introduction.html#why-learn-r"><i class="fa fa-check"></i><b>1.2</b> Why Learn R?</a>
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<li class="chapter" data-level="1.2.1" data-path="introduction.html"><a href="introduction.html#flexibility-and-power"><i class="fa fa-check"></i><b>1.2.1</b> Flexibility and Power</a></li>
<li class="chapter" data-level="1.2.2" data-path="introduction.html"><a href="introduction.html#reproducibility"><i class="fa fa-check"></i><b>1.2.2</b> Reproducibility</a></li>
<li class="chapter" data-level="1.2.3" data-path="introduction.html"><a href="introduction.html#extensive-community-and-package-ecosystem"><i class="fa fa-check"></i><b>1.2.3</b> Extensive Community and Package Ecosystem</a></li>
<li class="chapter" data-level="1.2.4" data-path="introduction.html"><a href="introduction.html#cost"><i class="fa fa-check"></i><b>1.2.4</b> Cost</a></li>
</ul></li>
<li class="chapter" data-level="1.3" data-path="introduction.html"><a href="introduction.html#replicating-spss-functionality-in-r"><i class="fa fa-check"></i><b>1.3</b> Replicating SPSS Functionality in R</a>
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<li class="chapter" data-level="1.3.1" data-path="introduction.html"><a href="introduction.html#data-management"><i class="fa fa-check"></i><b>1.3.1</b> Data Management</a></li>
<li class="chapter" data-level="1.3.2" data-path="introduction.html"><a href="introduction.html#descriptive-statistics"><i class="fa fa-check"></i><b>1.3.2</b> Descriptive Statistics</a></li>
<li class="chapter" data-level="1.3.3" data-path="introduction.html"><a href="introduction.html#statistical-tests"><i class="fa fa-check"></i><b>1.3.3</b> Statistical Tests</a></li>
<li class="chapter" data-level="1.3.4" data-path="introduction.html"><a href="introduction.html#regression-analysis"><i class="fa fa-check"></i><b>1.3.4</b> Regression Analysis</a></li>
<li class="chapter" data-level="1.3.5" data-path="introduction.html"><a href="introduction.html#data-visualisation"><i class="fa fa-check"></i><b>1.3.5</b> Data Visualisation</a></li>
</ul></li>
<li class="chapter" data-level="1.4" data-path="introduction.html"><a href="introduction.html#transitioning-from-spss-to-r"><i class="fa fa-check"></i><b>1.4</b> Transitioning from SPSS to R</a>
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<li class="chapter" data-level="1.4.1" data-path="introduction.html"><a href="introduction.html#building-confidence-in-r"><i class="fa fa-check"></i><b>1.4.1</b> Building Confidence in R</a></li>
<li class="chapter" data-level="1.4.2" data-path="introduction.html"><a href="introduction.html#leveraging-rs-ecosystem"><i class="fa fa-check"></i><b>1.4.2</b> Leveraging R’s Ecosystem</a></li>
</ul></li>
<li class="chapter" data-level="1.5" data-path="introduction.html"><a href="introduction.html#conclusion"><i class="fa fa-check"></i><b>1.5</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html"><i class="fa fa-check"></i><b>2</b> Getting Started with R</a>
<ul>
<li class="chapter" data-level="2.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#the-r-environment"><i class="fa fa-check"></i><b>2.1</b> The R Environment</a>
<ul>
<li class="chapter" data-level="2.1.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#overview-of-the-rstudio-interface"><i class="fa fa-check"></i><b>2.1.1</b> Overview of the RStudio Interface</a></li>
<li class="chapter" data-level="2.1.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#console-vs.-scripts-vs.-notebooks"><i class="fa fa-check"></i><b>2.1.2</b> Console vs. Scripts vs. Notebooks</a></li>
</ul></li>
<li class="chapter" data-level="2.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#introduction-to-r-packages-and-installing-key-packages"><i class="fa fa-check"></i><b>2.2</b> Introduction to R Packages and Installing Key Packages</a>
<ul>
<li class="chapter" data-level="2.2.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#introduction-to-r-packages"><i class="fa fa-check"></i><b>2.2.1</b> Introduction to R Packages</a></li>
<li class="chapter" data-level="2.2.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#installing-and-loading-packages"><i class="fa fa-check"></i><b>2.2.2</b> Installing and Loading Packages</a></li>
<li class="chapter" data-level="2.2.3" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#key-packages-for-data-analysis"><i class="fa fa-check"></i><b>2.2.3</b> Key Packages for Data Analysis</a></li>
<li class="chapter" data-level="2.2.4" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#managing-package-dependencies"><i class="fa fa-check"></i><b>2.2.4</b> Managing Package Dependencies</a></li>
<li class="chapter" data-level="2.2.5" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#summary"><i class="fa fa-check"></i><b>2.2.5</b> Summary</a></li>
</ul></li>
<li class="chapter" data-level="2.3" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#coding-conventions-and-best-practices"><i class="fa fa-check"></i><b>2.3</b> Coding Conventions and Best Practices</a>
<ul>
<li class="chapter" data-level="2.3.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#writing-clean-and-readable-code"><i class="fa fa-check"></i><b>2.3.1</b> Writing Clean and Readable Code</a></li>
<li class="chapter" data-level="2.3.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#commenting-and-structuring-scripts"><i class="fa fa-check"></i><b>2.3.2</b> Commenting and Structuring Scripts</a></li>
</ul></li>
<li class="chapter" data-level="2.4" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#data-types-and-structures"><i class="fa fa-check"></i><b>2.4</b> Data Types and Structures</a>
<ul>
<li class="chapter" data-level="2.4.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#introduction-to-vectors-data-frames-lists-and-factors"><i class="fa fa-check"></i><b>2.4.1</b> Introduction to Vectors, Data Frames, Lists, and Factors</a></li>
<li class="chapter" data-level="2.4.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#comparing-r-data-types-to-spss-data-types"><i class="fa fa-check"></i><b>2.4.2</b> Comparing R Data Types to SPSS Data Types</a></li>
</ul></li>
<li class="chapter" data-level="2.5" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#basic-operations-and-functions-in-r"><i class="fa fa-check"></i><b>2.5</b> Basic Operations and Functions in R</a>
<ul>
<li class="chapter" data-level="2.5.1" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#arithmetic-operations"><i class="fa fa-check"></i><b>2.5.1</b> Arithmetic Operations</a></li>
<li class="chapter" data-level="2.5.2" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#logical-operations"><i class="fa fa-check"></i><b>2.5.2</b> Logical Operations</a></li>
<li class="chapter" data-level="2.5.3" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#basic-functions"><i class="fa fa-check"></i><b>2.5.3</b> Basic Functions</a></li>
</ul></li>
<li class="chapter" data-level="2.6" data-path="getting-started-with-r.html"><a href="getting-started-with-r.html#conclusion-1"><i class="fa fa-check"></i><b>2.6</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="3" data-path="data-management-in-r.html"><a href="data-management-in-r.html"><i class="fa fa-check"></i><b>3</b> Data Management in R</a>
<ul>
<li class="chapter" data-level="3.1" data-path="data-management-in-r.html"><a href="data-management-in-r.html#data-import-and-export"><i class="fa fa-check"></i><b>3.1</b> Data Import and Export</a>
<ul>
<li class="chapter" data-level="3.1.1" data-path="data-management-in-r.html"><a href="data-management-in-r.html#importing-data"><i class="fa fa-check"></i><b>3.1.1</b> Importing Data</a></li>
<li class="chapter" data-level="3.1.2" data-path="data-management-in-r.html"><a href="data-management-in-r.html#exporting-data"><i class="fa fa-check"></i><b>3.1.2</b> Exporting Data</a></li>
</ul></li>
<li class="chapter" data-level="3.2" data-path="data-management-in-r.html"><a href="data-management-in-r.html#data-cleaning-and-preparation"><i class="fa fa-check"></i><b>3.2</b> Data Cleaning and Preparation</a>
<ul>
<li class="chapter" data-level="3.2.1" data-path="data-management-in-r.html"><a href="data-management-in-r.html#handling-missing-data"><i class="fa fa-check"></i><b>3.2.1</b> Handling Missing Data</a></li>
<li class="chapter" data-level="3.2.2" data-path="data-management-in-r.html"><a href="data-management-in-r.html#filtering-and-subsetting-data"><i class="fa fa-check"></i><b>3.2.2</b> Filtering and Subsetting Data</a></li>
<li class="chapter" data-level="3.2.3" data-path="data-management-in-r.html"><a href="data-management-in-r.html#data-transformations"><i class="fa fa-check"></i><b>3.2.3</b> Data Transformations</a></li>
<li class="chapter" data-level="3.2.4" data-path="data-management-in-r.html"><a href="data-management-in-r.html#the-dplyr-pipeline"><i class="fa fa-check"></i><b>3.2.4</b> The dplyr Pipeline</a></li>
</ul></li>
<li class="chapter" data-level="3.3" data-path="data-management-in-r.html"><a href="data-management-in-r.html#working-with-categorical-data"><i class="fa fa-check"></i><b>3.3</b> Working with Categorical Data</a>
<ul>
<li class="chapter" data-level="3.3.1" data-path="data-management-in-r.html"><a href="data-management-in-r.html#creating-and-manipulating-factors"><i class="fa fa-check"></i><b>3.3.1</b> Creating and Manipulating Factors</a></li>
<li class="chapter" data-level="3.3.2" data-path="data-management-in-r.html"><a href="data-management-in-r.html#recoding-variables"><i class="fa fa-check"></i><b>3.3.2</b> Recoding Variables</a></li>
<li class="chapter" data-level="3.3.3" data-path="data-management-in-r.html"><a href="data-management-in-r.html#frequency-tables-and-cross-tabulations"><i class="fa fa-check"></i><b>3.3.3</b> Frequency Tables and Cross-Tabulations</a></li>
</ul></li>
<li class="chapter" data-level="3.4" data-path="data-management-in-r.html"><a href="data-management-in-r.html#conclusion-2"><i class="fa fa-check"></i><b>3.4</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="4" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html"><i class="fa fa-check"></i><b>4</b> Connecting to and Accessing a PostgreSQL Database</a>
<ul>
<li class="chapter" data-level="4.1" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#introduction-1"><i class="fa fa-check"></i><b>4.1</b> Introduction</a></li>
<li class="chapter" data-level="4.2" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#setting-up-the-environment"><i class="fa fa-check"></i><b>4.2</b> Setting Up the Environment</a>
<ul>
<li class="chapter" data-level="4.2.1" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#installing-necessary-packages"><i class="fa fa-check"></i><b>4.2.1</b> Installing Necessary Packages</a></li>
</ul></li>
<li class="chapter" data-level="4.3" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#connecting-to-postgresql-using-rpostgres"><i class="fa fa-check"></i><b>4.3</b> Connecting to PostgreSQL (Using RPostgres)</a></li>
<li class="chapter" data-level="4.4" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#querying-data-from-postgresql"><i class="fa fa-check"></i><b>4.4</b> Querying Data from PostgreSQL</a>
<ul>
<li class="chapter" data-level="4.4.1" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#executing-a-query"><i class="fa fa-check"></i><b>4.4.1</b> Executing a Query</a></li>
</ul></li>
<li class="chapter" data-level="4.5" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#handling-errors-and-troubleshooting"><i class="fa fa-check"></i><b>4.5</b> Handling Errors and Troubleshooting</a></li>
<li class="chapter" data-level="4.6" data-path="connecting-to-and-accessing-a-postgresql-database.html"><a href="connecting-to-and-accessing-a-postgresql-database.html#conclusion-3"><i class="fa fa-check"></i><b>4.6</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="5" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html"><i class="fa fa-check"></i><b>5</b> Descriptive Statistics and Visualisations</a>
<ul>
<li class="chapter" data-level="5.1" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#introduction-to-descriptive-statistics"><i class="fa fa-check"></i><b>5.1</b> Introduction to Descriptive Statistics</a>
<ul>
<li class="chapter" data-level="5.1.1" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#understanding-descriptive-statistics"><i class="fa fa-check"></i><b>5.1.1</b> Understanding Descriptive Statistics</a></li>
<li class="chapter" data-level="5.1.2" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#basic-descriptive-statistics-in-r"><i class="fa fa-check"></i><b>5.1.2</b> Basic Descriptive Statistics in R</a></li>
</ul></li>
<li class="chapter" data-level="5.2" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#creating-visualisations-with-ggplot2"><i class="fa fa-check"></i><b>5.2</b> Creating Visualisations with ggplot2</a>
<ul>
<li class="chapter" data-level="5.2.1" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#introduction-to-ggplot2"><i class="fa fa-check"></i><b>5.2.1</b> Introduction to ggplot2</a></li>
<li class="chapter" data-level="5.2.2" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#creating-basic-plots"><i class="fa fa-check"></i><b>5.2.2</b> Creating Basic Plots</a></li>
<li class="chapter" data-level="5.2.3" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#customising-your-plots"><i class="fa fa-check"></i><b>5.2.3</b> Customising Your Plots</a></li>
</ul></li>
<li class="chapter" data-level="5.3" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#descriptive-statistics-with-dplyr"><i class="fa fa-check"></i><b>5.3</b> Descriptive Statistics with dplyr</a>
<ul>
<li class="chapter" data-level="5.3.1" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#using-dplyr-to-summarise-data"><i class="fa fa-check"></i><b>5.3.1</b> Using dplyr to Summarise Data</a></li>
<li class="chapter" data-level="5.3.2" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#combining-dplyr-with-ggplot2"><i class="fa fa-check"></i><b>5.3.2</b> Combining dplyr with ggplot2</a></li>
</ul></li>
<li class="chapter" data-level="5.4" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#advanced-visualisation-techniques"><i class="fa fa-check"></i><b>5.4</b> Advanced Visualisation Techniques</a>
<ul>
<li class="chapter" data-level="5.4.1" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#faceting"><i class="fa fa-check"></i><b>5.4.1</b> Faceting</a></li>
<li class="chapter" data-level="5.4.2" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#combining-multiple-geoms"><i class="fa fa-check"></i><b>5.4.2</b> Combining Multiple Geoms</a></li>
<li class="chapter" data-level="5.4.3" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#saving-your-plots"><i class="fa fa-check"></i><b>5.4.3</b> Saving Your Plots</a></li>
</ul></li>
<li class="chapter" data-level="5.5" data-path="descriptive-statistics-and-visualisations.html"><a href="descriptive-statistics-and-visualisations.html#conclusion-4"><i class="fa fa-check"></i><b>5.5</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="6" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html"><i class="fa fa-check"></i><b>6</b> Survey Analysis in R</a>
<ul>
<li class="chapter" data-level="6.1" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#introduction-to-survey-data"><i class="fa fa-check"></i><b>6.1</b> Introduction to Survey Data</a>
<ul>
<li class="chapter" data-level="6.1.1" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#key-concepts-in-survey-analysis"><i class="fa fa-check"></i><b>6.1.1</b> Key Concepts in Survey Analysis</a></li>
<li class="chapter" data-level="6.1.2" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#understanding-survey-data-structures"><i class="fa fa-check"></i><b>6.1.2</b> Understanding Survey Data Structures</a></li>
</ul></li>
<li class="chapter" data-level="6.2" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#importing-and-preparing-survey-data"><i class="fa fa-check"></i><b>6.2</b> Importing and Preparing Survey Data</a>
<ul>
<li class="chapter" data-level="6.2.1" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#converting-data-for-survey-analysis"><i class="fa fa-check"></i><b>6.2.1</b> Converting Data for Survey Analysis</a></li>
</ul></li>
<li class="chapter" data-level="6.3" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#descriptive-analysis-of-survey-data"><i class="fa fa-check"></i><b>6.3</b> Descriptive Analysis of Survey Data</a>
<ul>
<li class="chapter" data-level="6.3.1" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#calculating-means-and-totals"><i class="fa fa-check"></i><b>6.3.1</b> Calculating Means and Totals</a></li>
<li class="chapter" data-level="6.3.2" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#frequencies-and-cross-tabulations"><i class="fa fa-check"></i><b>6.3.2</b> Frequencies and Cross-tabulations</a></li>
<li class="chapter" data-level="6.3.3" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#comparing-results-with-spss-survey-functions"><i class="fa fa-check"></i><b>6.3.3</b> Comparing Results with SPSS Survey Functions</a></li>
</ul></li>
<li class="chapter" data-level="6.4" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#weighting-survey-data"><i class="fa fa-check"></i><b>6.4</b> Weighting Survey Data</a>
<ul>
<li class="chapter" data-level="6.4.1" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#applying-weights"><i class="fa fa-check"></i><b>6.4.1</b> Applying Weights</a></li>
<li class="chapter" data-level="6.4.2" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#analysing-weighted-survey-data"><i class="fa fa-check"></i><b>6.4.2</b> Analysing Weighted Survey Data</a></li>
</ul></li>
<li class="chapter" data-level="6.5" data-path="survey-analysis-in-r.html"><a href="survey-analysis-in-r.html#conclusion-5"><i class="fa fa-check"></i><b>6.5</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="7" data-path="inferential-statistics.html"><a href="inferential-statistics.html"><i class="fa fa-check"></i><b>7</b> Inferential Statistics</a>
<ul>
<li class="chapter" data-level="7.1" data-path="inferential-statistics.html"><a href="inferential-statistics.html#hypothesis-testing"><i class="fa fa-check"></i><b>7.1</b> Hypothesis Testing</a>
<ul>
<li class="chapter" data-level="7.1.1" data-path="inferential-statistics.html"><a href="inferential-statistics.html#t-tests"><i class="fa fa-check"></i><b>7.1.1</b> T-tests</a></li>
<li class="chapter" data-level="7.1.2" data-path="inferential-statistics.html"><a href="inferential-statistics.html#chi-square-tests"><i class="fa fa-check"></i><b>7.1.2</b> Chi-square Tests</a></li>
<li class="chapter" data-level="7.1.3" data-path="inferential-statistics.html"><a href="inferential-statistics.html#anova-analysis-of-variance"><i class="fa fa-check"></i><b>7.1.3</b> ANOVA (Analysis of Variance)</a></li>
</ul></li>
<li class="chapter" data-level="7.2" data-path="inferential-statistics.html"><a href="inferential-statistics.html#correlation-analysis"><i class="fa fa-check"></i><b>7.2</b> Correlation Analysis</a>
<ul>
<li class="chapter" data-level="7.2.1" data-path="inferential-statistics.html"><a href="inferential-statistics.html#pearson-correlation"><i class="fa fa-check"></i><b>7.2.1</b> Pearson Correlation</a></li>
<li class="chapter" data-level="7.2.2" data-path="inferential-statistics.html"><a href="inferential-statistics.html#spearman-correlation"><i class="fa fa-check"></i><b>7.2.2</b> Spearman Correlation</a></li>
<li class="chapter" data-level="7.2.3" data-path="inferential-statistics.html"><a href="inferential-statistics.html#pearson-vs-spearman"><i class="fa fa-check"></i><b>7.2.3</b> Pearson vs Spearman?</a></li>
<li class="chapter" data-level="7.2.4" data-path="inferential-statistics.html"><a href="inferential-statistics.html#visualising-correlations"><i class="fa fa-check"></i><b>7.2.4</b> Visualising Correlations</a></li>
</ul></li>
<li class="chapter" data-level="7.3" data-path="inferential-statistics.html"><a href="inferential-statistics.html#conclusion-6"><i class="fa fa-check"></i><b>7.3</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="8" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html"><i class="fa fa-check"></i><b>8</b> Regression Analysis</a>
<ul>
<li class="chapter" data-level="8.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#introduction-to-regression-analysis"><i class="fa fa-check"></i><b>8.1</b> Introduction to Regression Analysis</a>
<ul>
<li class="chapter" data-level="8.1.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#what-is-linear-regression"><i class="fa fa-check"></i><b>8.1.1</b> What is Linear Regression?</a></li>
</ul></li>
<li class="chapter" data-level="8.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#simple-linear-regression-in-r"><i class="fa fa-check"></i><b>8.2</b> Simple Linear Regression in R</a>
<ul>
<li class="chapter" data-level="8.2.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#performing-simple-linear-regression"><i class="fa fa-check"></i><b>8.2.1</b> Performing Simple Linear Regression</a></li>
<li class="chapter" data-level="8.2.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#interpreting-the-output"><i class="fa fa-check"></i><b>8.2.2</b> Interpreting the Output</a></li>
</ul></li>
<li class="chapter" data-level="8.3" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#multiple-linear-regression"><i class="fa fa-check"></i><b>8.3</b> Multiple Linear Regression</a>
<ul>
<li class="chapter" data-level="8.3.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#performing-multiple-linear-regression"><i class="fa fa-check"></i><b>8.3.1</b> Performing Multiple Linear Regression</a></li>
<li class="chapter" data-level="8.3.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#detailed-interpretation-of-the-output"><i class="fa fa-check"></i><b>8.3.2</b> Detailed Interpretation of the Output</a></li>
</ul></li>
<li class="chapter" data-level="8.4" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#checking-model-assumptions"><i class="fa fa-check"></i><b>8.4</b> Checking Model Assumptions</a>
<ul>
<li class="chapter" data-level="8.4.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-1-linearity"><i class="fa fa-check"></i><b>8.4.1</b> Assumption 1: Linearity</a></li>
<li class="chapter" data-level="8.4.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-2-normality-of-residuals"><i class="fa fa-check"></i><b>8.4.2</b> Assumption 2: Normality of Residuals</a></li>
<li class="chapter" data-level="8.4.3" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-3-homoscedasticity"><i class="fa fa-check"></i><b>8.4.3</b> Assumption 3: Homoscedasticity</a></li>
<li class="chapter" data-level="8.4.4" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-4-independence-of-errors"><i class="fa fa-check"></i><b>8.4.4</b> Assumption 4: Independence of Errors</a></li>
<li class="chapter" data-level="8.4.5" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-5-multicollinearity"><i class="fa fa-check"></i><b>8.4.5</b> Assumption 5: Multicollinearity</a></li>
</ul></li>
<li class="chapter" data-level="8.5" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#transformations-and-interaction-terms"><i class="fa fa-check"></i><b>8.5</b> Transformations and Interaction Terms</a>
<ul>
<li class="chapter" data-level="8.5.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#when-and-how-to-apply-transformations"><i class="fa fa-check"></i><b>8.5.1</b> When and How to Apply Transformations</a></li>
<li class="chapter" data-level="8.5.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#using-interaction-terms"><i class="fa fa-check"></i><b>8.5.2</b> Using Interaction Terms</a></li>
</ul></li>
<li class="chapter" data-level="8.6" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#logistic-regression"><i class="fa fa-check"></i><b>8.6</b> Logistic Regression</a>
<ul>
<li class="chapter" data-level="8.6.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#performing-logistic-regression-in-r"><i class="fa fa-check"></i><b>8.6.1</b> Performing Logistic Regression in R</a></li>
<li class="chapter" data-level="8.6.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#interpreting-logistic-regression-output"><i class="fa fa-check"></i><b>8.6.2</b> Interpreting Logistic Regression Output</a></li>
</ul></li>
<li class="chapter" data-level="8.7" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#checking-model-assumptions-for-logistic-regression"><i class="fa fa-check"></i><b>8.7</b> Checking Model Assumptions for Logistic Regression</a>
<ul>
<li class="chapter" data-level="8.7.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-1-linearity-of-the-logit"><i class="fa fa-check"></i><b>8.7.1</b> Assumption 1: Linearity of the Logit</a></li>
<li class="chapter" data-level="8.7.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-2-independence-of-observations"><i class="fa fa-check"></i><b>8.7.2</b> Assumption 2: Independence of Observations</a></li>
<li class="chapter" data-level="8.7.3" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-3-absence-of-multicollinearity"><i class="fa fa-check"></i><b>8.7.3</b> Assumption 3: Absence of Multicollinearity</a></li>
<li class="chapter" data-level="8.7.4" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#assumption-4-sufficient-sample-size"><i class="fa fa-check"></i><b>8.7.4</b> Assumption 4: Sufficient Sample Size</a></li>
</ul></li>
<li class="chapter" data-level="8.8" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#model-validation-and-diagnostics"><i class="fa fa-check"></i><b>8.8</b> Model Validation and Diagnostics</a>
<ul>
<li class="chapter" data-level="8.8.1" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#cross-validation"><i class="fa fa-check"></i><b>8.8.1</b> Cross-Validation</a></li>
<li class="chapter" data-level="8.8.2" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#dealing-with-overfitting"><i class="fa fa-check"></i><b>8.8.2</b> Dealing with Overfitting</a></li>
</ul></li>
<li class="chapter" data-level="8.9" data-path="regression-analysis-1.html"><a href="regression-analysis-1.html#conclusion-7"><i class="fa fa-check"></i><b>8.9</b> Conclusion</a></li>
</ul></li>
<li class="chapter" data-level="9" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html"><i class="fa fa-check"></i><b>9</b> Geographic Mapping and Spatial Analysis</a>
<ul>
<li class="chapter" data-level="9.1" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#introduction-to-geographic-data-in-r"><i class="fa fa-check"></i><b>9.1</b> Introduction to Geographic Data in R</a>
<ul>
<li class="chapter" data-level="9.1.1" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#understanding-geographic-data-formats"><i class="fa fa-check"></i><b>9.1.1</b> Understanding Geographic Data Formats</a></li>
<li class="chapter" data-level="9.1.2" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#importing-and-handling-spatial-data-with-the-sf-package"><i class="fa fa-check"></i><b>9.1.2</b> Importing and Handling Spatial Data with the <code>sf</code> Package</a></li>
</ul></li>
<li class="chapter" data-level="9.2" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#geographic-coordinate-systems-and-projections"><i class="fa fa-check"></i><b>9.2</b> Geographic Coordinate Systems and Projections</a>
<ul>
<li class="chapter" data-level="9.2.1" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#introduction-to-coordinate-systems"><i class="fa fa-check"></i><b>9.2.1</b> Introduction to Coordinate Systems</a></li>
<li class="chapter" data-level="9.2.2" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#common-issues-with-coordinate-systems-in-r"><i class="fa fa-check"></i><b>9.2.2</b> Common Issues with Coordinate Systems in R</a></li>
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<li class="chapter" data-level="9.5" data-path="geographic-mapping-and-spatial-analysis.html"><a href="geographic-mapping-and-spatial-analysis.html#conclusion-8"><i class="fa fa-check"></i><b>9.5</b> Conclusion</a></li>
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<li class="chapter" data-level="" data-path="exercise-answers.html"><a href="exercise-answers.html#exercise-3.4"><i class="fa fa-check"></i>Exercise 3.4</a></li>
<li class="chapter" data-level="" data-path="exercise-answers.html"><a href="exercise-answers.html#exercise-3.5"><i class="fa fa-check"></i>Exercise 3.5</a></li>
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<li class="chapter" data-level="" data-path="exercise-answers.html"><a href="exercise-answers.html#exercise-3.7"><i class="fa fa-check"></i>Exercise 3.7</a></li>
<li class="chapter" data-level="" data-path="exercise-answers.html"><a href="exercise-answers.html#exercise-3.8"><i class="fa fa-check"></i>Exercise 3.8</a></li>
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<i class="fa fa-circle-o-notch fa-spin"></i><a href="./">Introduction to R for Crime Analysts</a>
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<div id="introduction" class="section level1 hasAnchor" number="1">
<h1><span class="header-section-number">1</span> Introduction<a href="introduction.html#introduction" class="anchor-section" aria-label="Anchor link to header"></a></h1>
<div id="overview" class="section level2 hasAnchor" number="1.1">
<h2><span class="header-section-number">1.1</span> Overview<a href="introduction.html#overview" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>In the world of data analysis, the choice of software can significantly impact the flexibility, efficiency, and depth of your analyses. For many years, SPSS has been a popular tool among social scientists, market researchers, and others who require a straightforward interface for statistical analysis. However, as data analysis becomes more complex and expansive, many analysts are turning to R, an open-source programming language and environment that offers unparalleled flexibility, a vast array of packages, and a growing community of users.</p>
<p>This course is designed to help you transition from SPSS to R, demonstrating that all of the functionality you’re accustomed to in SPSS can be replicated—and often enhanced—in R. By the end of this course, you will be equipped with the knowledge and skills to conduct your analyses in R, whether you’re dealing with basic descriptive statistics, survey data, or more advanced statistical models.</p>
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<div id="why-learn-r" class="section level2 hasAnchor" number="1.2">
<h2><span class="header-section-number">1.2</span> Why Learn R?<a href="introduction.html#why-learn-r" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<div id="flexibility-and-power" class="section level3 hasAnchor" number="1.2.1">
<h3><span class="header-section-number">1.2.1</span> Flexibility and Power<a href="introduction.html#flexibility-and-power" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>R is a full-fledged programming language, which means it is inherently more flexible than SPSS. While SPSS provides a user-friendly interface with point-and-click options, R allows for a deeper level of customisation and control over your analyses. You can automate tasks, create reproducible reports, and even develop new statistical methods if needed.</p>
<p><strong>Example:</strong> In SPSS, you might run a regression using a dialog box and then manually record the output. In R, you can automate this process, run multiple regressions in a loop, and automatically output the results to a report.</p>
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<div id="reproducibility" class="section level3 hasAnchor" number="1.2.2">
<h3><span class="header-section-number">1.2.2</span> Reproducibility<a href="introduction.html#reproducibility" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>Reproducibility is a cornerstone of modern data analysis. R’s script-based workflow ensures that every step of your analysis is documented, making it easy to reproduce results or adjust your analysis if new data becomes available. This contrasts with SPSS, where much of the analysis is done through a GUI, making it harder to track and reproduce each step without explicitly saving syntax files.</p>
<p><strong>Example: </strong> In R, you can save your entire analysis pipeline in a script, which can be rerun with new data or shared with colleagues for replication.</p>
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<div id="extensive-community-and-package-ecosystem" class="section level3 hasAnchor" number="1.2.3">
<h3><span class="header-section-number">1.2.3</span> Extensive Community and Package Ecosystem<a href="introduction.html#extensive-community-and-package-ecosystem" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>One of R’s greatest strengths is its vast and active community, which has contributed thousands of packages to CRAN (the Comprehensive R Archive Network). Whether you need advanced statistical techniques, machine learning algorithms, or specialised visualisations, there’s likely an R package available. This is in contrast to SPSS, where functionality is often limited to what is provided out-of-the-box or through costly add-ons.</p>
<p><strong>Example:</strong> In R, you might use the ggplot2 package for advanced visualisations, dplyr for data manipulation, or survey for complex survey analysis. In SPSS, creating custom visualisations or handling complex survey designs might require more manual effort or external software.</p>
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<div id="cost" class="section level3 hasAnchor" number="1.2.4">
<h3><span class="header-section-number">1.2.4</span> Cost<a href="introduction.html#cost" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>R is completely free and open-source, which is a significant advantage over SPSS, especially for organisations with budget constraints. This means you can install R on as many computers as you need, share it with colleagues, and access the latest updates and packages without any cost.</p>
<p><strong>Example:</strong> Many organisations are moving to R not only because of its capabilities but also because it reduces software costs significantly.</p>
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<div id="replicating-spss-functionality-in-r" class="section level2 hasAnchor" number="1.3">
<h2><span class="header-section-number">1.3</span> Replicating SPSS Functionality in R<a href="introduction.html#replicating-spss-functionality-in-r" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>If you’re used to SPSS, the idea of switching to a command-line-driven environment might seem daunting. However, you’ll find that every major feature of SPSS can be replicated in R—often with greater flexibility and power.</p>
<div id="data-management" class="section level3 hasAnchor" number="1.3.1">
<h3><span class="header-section-number">1.3.1</span> Data Management<a href="introduction.html#data-management" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>In SPSS, data management tasks such as merging datasets, recoding variables, or selecting cases are performed using a series of dialog boxes or syntax commands. In R, these tasks are handled with functions and packages like dplyr, which offer intuitive syntax for manipulating data.</p>
<p><strong>Example:</strong> Recoding variables in SPSS might require several steps in the GUI, while in R, you can accomplish the same with a single line of code using mutate() and case_when().</p>
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<div id="descriptive-statistics" class="section level3 hasAnchor" number="1.3.2">
<h3><span class="header-section-number">1.3.2</span> Descriptive Statistics<a href="introduction.html#descriptive-statistics" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>Both SPSS and R allow you to calculate descriptive statistics such as means, medians, and standard deviations. In R, you can use basic functions like mean() and sd(), or you can employ packages like psych or skimr for more detailed summaries.</p>
<p><strong>Example:</strong> Descriptive statistics in SPSS are often displayed in tables generated by the <code>DESCRIPTIVES</code> command, whereas in R, you can achieve this with a simple script, and even automate it for multiple variables.</p>
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<div id="statistical-tests" class="section level3 hasAnchor" number="1.3.3">
<h3><span class="header-section-number">1.3.3</span> Statistical Tests<a href="introduction.html#statistical-tests" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>SPSS is known for its user-friendly interfaces for running statistical tests. In R, all the same tests (t-tests, ANOVA, chi-square, etc.) are available, and you can conduct them using straightforward commands.</p>
<p><strong>Example:</strong> Running a t-test in SPSS involves navigating through multiple menus, while in R, the same test can be executed with a simple t.test() function.</p>
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<div id="regression-analysis" class="section level3 hasAnchor" number="1.3.4">
<h3><span class="header-section-number">1.3.4</span> Regression Analysis<a href="introduction.html#regression-analysis" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>Regression analysis, a staple of SPSS, is fully supported in R. Whether you’re running simple linear regressions or more complex logistic regressions, R provides the tools you need. The <code>lm()</code> function is used for linear models, while <code>glm()</code> handles generalised linear models, including logistic regression.</p>
<p><strong>Example:</strong> In SPSS, you might need to manually specify each option in the regression dialog box. In R, you have the flexibility to customise your models directly in code, making it easy to adjust your analysis as needed.</p>
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<div id="data-visualisation" class="section level3 hasAnchor" number="1.3.5">
<h3><span class="header-section-number">1.3.5</span> Data Visualisation<a href="introduction.html#data-visualisation" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>While SPSS provides basic charting capabilities, R, with its ggplot2 package, is unmatched in the realm of data visualisation. You can create everything from simple bar charts to complex multi-faceted plots, with full control over every aspect of the appearance.</p>
<p><strong>Example:</strong> A simple bar chart in SPSS might look quite basic, whereas in R, you can use ggplot2 to add layers, colors, themes, and annotations to create publication-quality graphics.</p>
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<div id="transitioning-from-spss-to-r" class="section level2 hasAnchor" number="1.4">
<h2><span class="header-section-number">1.4</span> Transitioning from SPSS to R<a href="introduction.html#transitioning-from-spss-to-r" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Transitioning from SPSS to R might feel like a big leap, but with the right guidance, you’ll soon see how R’s power and flexibility make it a worthwhile switch. Throughout this book, we will replicate common SPSS procedures in R, step by step. You’ll see how to import your data, perform the same analyses you’re used to, and even go beyond what SPSS can offer.</p>
<div id="building-confidence-in-r" class="section level3 hasAnchor" number="1.4.1">
<h3><span class="header-section-number">1.4.1</span> Building Confidence in R<a href="introduction.html#building-confidence-in-r" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>We’ll start with simple tasks, such as descriptive statistics and data manipulation, gradually moving to more advanced topics like regression analysis and survey data handling. By building on your existing knowledge of SPSS, you’ll find that learning R is not as daunting as it might seem.</p>
<p><strong>Example:</strong> We’ll compare SPSS and R workflows for common tasks, showing how R can simplify and enhance your analytical processes.</p>
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<div id="leveraging-rs-ecosystem" class="section level3 hasAnchor" number="1.4.2">
<h3><span class="header-section-number">1.4.2</span> Leveraging R’s Ecosystem<a href="introduction.html#leveraging-rs-ecosystem" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>One of the goals of this course is to familiarise you with the rich ecosystem of R packages. We’ll introduce you to some of the most useful packages for data analysis, showing how they can replace or enhance the tools you’re used to in SPSS.</p>
<p><strong>Example:</strong> For instance, you’ll see how <code>dplyr</code> can streamline your data manipulation tasks, or how <code>ggplot2</code> can elevate your data visualisation.</p>
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<div id="conclusion" class="section level2 hasAnchor" number="1.5">
<h2><span class="header-section-number">1.5</span> Conclusion<a href="introduction.html#conclusion" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>As you proceed through this course, you’ll gain the skills needed to replicate and enhance the analyses you currently perform in SPSS. Each chapter will build on the previous ones, gradually expanding your knowledge and capabilities in R. By the end of this book, you’ll be able to handle all your data analysis tasks in R with confidence, taking full advantage of its flexibility, power, and vast ecosystem of packages.</p>
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