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Introduction to R

Basic R syntax

Nicole Baerg

This guided project is for beginners interested in taking their first steps with coding in the statistical language R. It assumes no previous knowledge of R, introduces the RStudio environment, and covers basic concepts, tools, and general syntax. By the end of the exercise, learners will build familiarity with RStudio and the fundamentals of the statistical coding language R.

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What's inside

Syllabus

Project Overview

By the end of this project, you will understand basic R syntax, objects, importing and exporting. You will learn how to run arithmetic operations in R, how to create objects, vectors, text, use logical operators, and functions. This project is aimed at complete beginners who have no previous experience in R or RStudio, or people with a small amount of experience who would like to review the fundamental building blocks of the R language.

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Introduces beginners to the RStudio environment, basic concepts, and syntax

Assumes no prior knowledge of R

Covers basic concepts, tools, and general syntax

Teaches how to run arithmetic operations, create objects, vectors, text, use logical operators, and functions

Suitable for complete beginners with no previous experience in R or RStudio

May be useful for individuals with some experience who want to review the fundamentals

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Reviews summary

Easygoing r crash course

Learners say this introductory course to R provides quality content, but the material is limited. Students report that it provides a good review of R skills and clarifies R's benefits over applications like EXCEL.

The course is good for a review of R skills.

"An appropriate step to review, building multiple approaches to known skills, and my CPN journey. "

The course could clarify R's benefits.

"It's good to clarify what are the benefits/differences to other applications like using EXCEL as we are beginners."

The course has just enough materials.

"The content was less than I expected but quality over quantity."

"Good introduction for someone who wants to get the ghist of this programming language."

The course is short on content.

"There is hardly any material."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to R: Basic R syntax with these activities:

Connect with experienced R users

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Provides access to expert guidance and support

Browse courses on R Programming

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Attend R meetups or conferences
Reach out to R developers on social media or online forums

Read R for Data Science

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Provides a comprehensive overview of R for data science

View R for Data Science: Import, Tidy, Transform,... on Amazon

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Read the book and complete the exercises

Review basic statistics concepts

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Reviews core concepts that will aid learning R

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Revisit basic concepts like measures of central tendency and variation
Consider reviewing a statistics textbook or online resources

Six other activities

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Complete RStudio tutorial

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Provides a structured way to learn the RStudio environment

Browse courses on RStudio

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Follow the official RStudio tutorial
Complete the exercises and quizzes provided in the tutorial

Create a cheat sheet of R commands

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Helps memorize and recall important R commands

Browse courses on R Programming

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Identify commonly used R commands
Create a cheat sheet summarizing these commands and their usage

Practice R syntax

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Reinforces understanding of R syntax and commands

Browse courses on R Programming

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Find online exercises or coding challenges
Practice writing R code to solve problems

Join a study group

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Provides opportunities to collaborate and learn from peers

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Find a study group or create your own
Meet regularly to discuss course material and work on problems together

Build a simple data analysis project

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Applies R skills to a practical project, reinforcing learning

Browse courses on Data Analysis

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Choose a small dataset and research question
Clean and explore the data
Perform statistical analysis and create visualizations

Present your R project findings

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Encourages effective communication of R findings

Browse courses on Data Analysis

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Prepare a presentation summarizing your project
Present your findings to your classmates or a wider audience

Career center

Learners who complete Introduction to R: Basic R syntax will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts play a crucial role in making sense of vast amounts of data. This course provides a solid foundation for understanding R, a statistical coding language widely used by Data Analysts. By mastering the basics of R syntax, importing and exporting data, arithmetic operations, and creating objects, learners can enhance their data analysis skills and prepare for a successful career in this field.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians utilize statistical techniques to analyze data and draw meaningful conclusions. This course introduces the fundamentals of R, a powerful tool for statistical analysis. By gaining proficiency in basic R syntax, creating objects, and using logical operators, learners can build a strong foundation for success as Statisticians.

See salaries and explore the career path for Statistician

Data Scientist

Data Scientists combine expertise in data analysis, statistics, and machine learning to solve complex business problems. This course provides an essential introduction to R, a key programming language in the field. Through hands-on exercises in importing data, creating objects, and performing arithmetic operations, learners can develop skills necessary for a thriving career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models. This course lays the groundwork for success in this field by introducing the basics of R, a language commonly used for building and deploying machine learning models. Learners will gain hands-on experience in creating R objects, understanding logical operators, and performing arithmetic operations, providing a valuable stepping stone for a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Research Analyst

Research Analysts conduct data-driven research to support decision-making. This course provides a strong foundation for this role by introducing R, a statistical programming language widely used in research. By learning basic R syntax, creating objects, and using logical operators, learners can build a solid understanding of data analysis techniques essential for success as Research Analysts.

See salaries and explore the career path for Research Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. While not a direct fit, this course can provide a foundation for those interested in exploring data analysis and statistical programming. By understanding basic R syntax, creating objects, and using logical operators, learners can gain insights into the use of coding languages in software engineering.

See salaries and explore the career path for Software Engineer

Business Analyst

Business Analysts use data and analysis to solve business problems and improve decision-making. This course provides an introductory understanding of R, a powerful tool for data analysis. By mastering basic R syntax, creating objects, and using logical operators, learners can develop skills applicable to a career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course provides a strong foundation for this role by introducing R, a statistical programming language widely used in finance. By gaining proficiency in basic R syntax, creating objects, and using logical operators, learners can develop skills essential for a successful career as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course provides a valuable introduction to R, a statistical programming language commonly used in actuarial science. By understanding basic R syntax, creating objects, and using logical operators, learners can build a foundation for success in this field.

See salaries and explore the career path for Actuary

Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. While not a direct fit, this course can provide a foundation for those interested in exploring data analysis. By understanding basic R syntax, creating objects, and using logical operators, learners can gain insights into the use of coding languages in data engineering.

See salaries and explore the career path for Data Engineer

Financial Analyst

Financial Analysts use financial data to make investment recommendations and advise clients. This course provides a basic understanding of R, a statistical programming language used in financial analysis. By learning R syntax, creating objects, and using logical operators, learners can develop skills applicable to a career as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market Researchers conduct research to understand consumer behavior and market trends. This course provides an introduction to R, a statistical programming language commonly used in market research. By mastering basic R syntax, creating objects, and using logical operators, learners can gain skills relevant to a career as a Market Researcher.

See salaries and explore the career path for Market Researcher

Epidemiologist

Epidemiologists study the distribution and patterns of health events in populations. This course provides a foundation for this role by introducing R, a statistical programming language widely used in epidemiology. By understanding basic R syntax, creating objects, and using logical operators, learners can develop skills essential for a successful career as an Epidemiologist.

See salaries and explore the career path for Epidemiologist

Biostatistician

Biostatisticians apply statistical methods to biological data. This course provides an introductory understanding of R, a statistical programming language commonly used in biostatistics. By learning basic R syntax, creating objects, and using logical operators, learners can build a foundation for success in this field.

See salaries and explore the career path for Biostatistician

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to improve decision-making in organizations. This course provides a foundation for this role by introducing R, a statistical programming language used in operations research. By understanding basic R syntax, creating objects, and using logical operators, learners can develop skills valuable for a career as an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to R: Basic R syntax.

R for Data Science

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Provides a comprehensive introduction to the R programming language and its use in data science. It covers a wide range of topics, from basic syntax to advanced data analysis techniques, including objected-oriented programming.

Introduction to R

Basic R syntax

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Easygoing r crash course

Activities

Career center

Reading list

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