Recommended Reading
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R for Data Science
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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. -
RStudio for R Statistical Computing Cookbook
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Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature.
Twitter is excellent for crowdsourcing, networking, and finding R-related resources. I highly recommend following these people in the R community:
R Ladies
R Ladies is a working group that promotes diversity in the #rstats community via meetups, mentorship, and global collaboration. There are over 90 groups worldwide. We have our own R Ladies group here at Vanderbilt. For updates and future meetups, follow them on Twitter and Meetup.
Downloading R/RStudio
- Download the R programming language here. You will need to download R before you download RStudio. Under "Download and Install R" make sure to click on your operating system (OS). If you're running on Windows, use Windows. If you're using Mac, use Mac. Click on base if you're downloading R for the first time. Continue to click through and accept the installation process.
- Download RStudio here. RStudio is R's graphic user interface (GUI). Essentially, RStudio is a more user-friendly way to program in R. Like downloading R, make sure to choose your correct OS under "Installers." Click on your correct installer and RStudio.exe will download.
- After you have both R and RStudio installed, open up RStudio:
- Done.
- In exchange for a course syllabus, any .edu academic can get any and all RStudio professional tools for free use in teaching.
- Academic researchers not involved in teaching get 50% off.
- Example of tools: RStudio's Server Pro, RStudio Connect, and RStudio package manager.
Why R?
R is a powerful, open source (free) programming language primarily used for statistical analysis and visualization. It is the second most popular language in data science.
Databases & Datasets
Use these resources to export data in tidy, tabulated format (.csv, .xlsx).
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Capital IQ (Owen and Law) This link opens in a new window
Available for members of the Owen and Law community. Financial data for public & private companies worldwide; private capital firms; M&A transactions. Financial analysis tools to generate reports: comparable analysis, market analysis, financial modeling, etc. First-time users must register for a personal account using their vanderbilt.edu email address.
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Hoovers This link opens in a new windowDetails on US and international companies, executives, market research reports, and trade publications. Includes financials, subsidiaries, and trade and business news.
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International Monetary Fund (IMF) Publications This link opens in a new windowLinks to the full text of recent IMF working papers, staff country reports, papers on policy analysis and assessment, and member country publications.
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Mintel Academic This link opens in a new window
Market research reports focused on consumers in the U.S., U.K., European, and some Asian markets. Market drivers, size & trends and segmentation; supply structure, advertising & promotion, retail distribution, consumer characteristics & forecasts.
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Passport Euromonitor This link opens in a new windowEuromonitor International's global market analysis software platform, providing industry information, consumer statistics and analysis, historical and forecast data, consumer trends and lifestyles, articles, company profiles, and global reports.
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PolicyMap This link opens in a new window
Data and mapping tool that provides access to over 15,000 indicators related to demographics, housing, crime, mortgages, health, jobs and more. Data is available at all common geographies (address, block group, census tract, zip code, county, city, state, MSA) as well as unique geographies like school districts and political boundaries. Create, save, download, customized maps and tables, or upload your own data to map.
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Sage Data This link opens in a new window
Dynamically compare and manipulate statistical data to create tables, maps, and figures.
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SimplyAnalytics This link opens in a new windowA mapping, analytics, and data visualization application that makes it easy for anyone to create interactive maps and reports using thousands of demographic, business, and marketing variables.
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Statista This link opens in a new window
Quantitative data, statistics, infographics, and related information compiled from market research institutes, trade publications, scientific journals, and government databases. Please note: To access the eCommerce Insights module within Statista, click Insights > Explore eCommerce Insights and then click Login from at the top right of the screen.
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Data.govThe Home of the U.S. Government's Open Data
Walker Management Library
Owen Graduate School of Management
401 21st. Avenue South
Nashville, TN 37203
R/RStudio Workshops: Based on "R for Data Science"
Additional R/RStudio Resources
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Learning Statistics with RThis repository contains all the source materials for Learning Statistics with R. There are two versions of the content, the original version (LSR v0.6) written in LaTeX and the bookdown adaptation (LSR v0.6.1). The two versions are kept in distinct folders to ensure they share no dependencies.
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Code and Slides for RStudio webinarsThis repository contains materials that have been used in official RStudio webinars.
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Data Science ToolkitThe purpose of this repository is to serve as stockpile of statistical methods, modeling techniques, and data science tools. The content itself includes everything from educational vignettes on specific topics, to tailored functions and modeling pipelines built to enhance and optimize analyses, to notes and code from various data science conferences, to general data science utilities.
