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2 changes: 1 addition & 1 deletion README.md
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layout: home
title: R for non-technical PhD students
title: R for non-Technical Researchers
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4 changes: 2 additions & 2 deletions _chapters/000-front/030-prologue.md
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In the modern age of data-driven decision-making, research is no longer confined to the realm of statisticians or computer scientists. The ability to analyze and interpret data is now a vital skill for scholars across all disciplines. From the social sciences to biology, economics to linguistics, the power to extract insights from data has transformed how we understand and shape the world.

Yet, for many researchers, the tools and techniques of data analysis can seem intimidating, particularly those without a technical background. Complex terminologies, steep learning curves, and a lack of accessible resources often create barriers for non-technical students and researchers who are eager to leverage the potential of data.
Yet, for many researchers, the tools and techniques of data analysis can seem intimidating, particularly those without a technical background. Complex terminologies, steep learning curves, and a lack of accessible resources often create barriers for non-technical researchers and researchers who are eager to leverage the potential of data.

This book, *R for Non-Technical PhD Students*, is written with you in mind. It serves as a bridge between the technical intricacies of data science and the practical needs of researchers in diverse fields. By using R—a powerful, open-source programming language tailored for statistical computing and data visualization—this book aims to make statistical and machine learning techniques accessible, approachable, and applicable to real-world research challenges.
This book, *R for Non-Technical Researchers*, is written with you in mind. It serves as a bridge between the technical intricacies of data science and the practical needs of researchers in diverse fields. By using R—a powerful, open-source programming language tailored for statistical computing and data visualization—this book aims to make statistical and machine learning techniques accessible, approachable, and applicable to real-world research challenges.

Through clear explanations, practical examples, and step-by-step guidance, this book demystifies the process of working with data in R. Whether you're a novice looking to understand basic statistical principles or a researcher seeking to incorporate machine learning into your work, this book will empower you to confidently analyze data and draw meaningful conclusions.

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2 changes: 1 addition & 1 deletion _chapters/000-front/050.introduction.md
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#### **Why This Book?**

The need for a comprehensive yet accessible guide to R for non-technical students and researchers is the driving force behind this book. *R for Non-Technical PhD Students* is not just another technical manual. It is a practical, hands-on resource tailored to the unique needs of those who want to leverage data without becoming overwhelmed by its technicalities.
The need for a comprehensive yet accessible guide to R for non-technical researchers and researchers is the driving force behind this book. *R for Non-Technical Researchers* is not just another technical manual. It is a practical, hands-on resource tailored to the unique needs of those who want to leverage data without becoming overwhelmed by its technicalities.

Many existing resources assume prior programming knowledge or delve too deeply into theoretical statistics. While these are invaluable for certain audiences, they can alienate readers who are new to both programming and advanced analytics. This book bridges the gap, offering a balanced approach that combines essential concepts with practical applications.

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# remote_theme: jasongrimes/jekyll-chapterbook

title: R4NTR
longtitle: R for Non-Technical PhD Students
longtitle: R for Non-Technical Researchers
author: Polla Fattah
email: [email protected]
description: >
This book aims to provide a comprehensive guide to the research for PhD students that seek to use R for their research.
The primary Audience for this book is non-technical students and researchers to introduce them with statistical analysis and data analysis using R.
This book aims to provide a comprehensive guide for the non-technical researchers that seek to use R for their research.
The primary Audience for this book is non-technical researchers and researchers to introduce them with statistical analysis and data analysis using R.
The book is designed to be a practical guide for researchers who are new to R and Programming in general.
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# Links shown above the TOC in the sidebar
# All "url" variables should have a leading slash.
sidebar_nav_top:
- label: R for Non-Technical PhD Students
- label: R for Non-Technical Researchers
url: /index.html

# Links shown below the TOC in the sidebar
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4 changes: 2 additions & 2 deletions index.md
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title: R for Non-Technical PhD Students (R4NTR)
title: R for Non-Technical Researchers (R4NTR)
permalink: /
layout: home
---

Last updated: {{ "now" | date: "%B %e, %Y" }}

Welcome to R for Non-Technical PhD Students (R4NTR), a comprehensive guide designed to empower researchers with limited technical backgrounds to harness the power of R for data analysis and statistical computing.
Welcome to R for Non-Technical Researchers (R4NTR), a comprehensive guide designed to empower researchers with limited technical backgrounds to harness the power of R for data analysis and statistical computing.

This book is a living document, continuously updated to ensure that its content stays relevant, accurate, and aligned with the latest advancements in R and its applications. Whether you're new to programming, exploring statistics, or diving into machine learning, this book provides the tools, techniques, and confidence you need to integrate R into your research journey effectively.

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