Hogg Award for For Excellence in Teaching Introductory Statistics. Mine is a Fellow of the ASA and Elected Member of the ISI as well as the winner of the 2021 Robert V. She is also the creator and maintainer of and she teaches the popular Statistics with R MOOC on Coursera. Learn R & Python with colleagues while working through a data science project relevant to your business. Posit Academy fixes this with a mentor-led apprenticeship that helps data professionals learn and apply skills relevant to the challenges they tackle every day. As part of this project she co-authored four open-source introductory statistics textbooks. Traditional data science training often fails to build lasting skills. Mine works on the OpenIntro project, whose mission is to make educational products that are free, transparent, and lower barriers to education. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. Links to download a pdf of the book and associated datasets can be found on the linked website.Mine Çetinkaya-Rundel is Professor of the Practice at Duke University and Developer Educator at RStudio. Focuses on mathematical statistics and explores real datasets using R with lines of code explained in detail. Lavine (2013) Introduction to Statistical Thought - intended as an upper level undergraduate or introductory graduate textbook for students with a good knowledge of calculus. (2014) Advanced R - Link is the companion website to the book and is designed primarily for intermediate R users and programmers from other languages. Datasets are also accessible via their website. Authors assume reader has had a previous course in linear regression and no knowledge of matrix algebra. (2014) An Introduction to Statistical Learning with Applications in R - Overview of statistical learning including important modeling and prediction techniques, along with relevant applications. Presenters come from companies around the globe, as well as the Posit staff. Grolemund and Wickham (2017) R for Data Science - open sourse eBook written for R begginersįaraway (2002) Practical Regression and ANOVA using R - Provides basic mathematical theory behind regression using R code and real datasets to explain the concepts Posits videos offer helpful perspective and vital information. R Manuals - Documentation from CRAN, the online repository for just about everything R R Style Guide - Whether you are just starting to code or consider yourself an expert, this site suggests how to write readable, maintainable code RStudio Cheat Sheets - Downloadable and printable reference guides for Base & Advanced R, RStudio IDE, R Markdown, Shiny, Data Viz, Package Development, among others R WIKIBOOKS - free online source that has contents listed on the right of the page and can be searched for content using the provided search box R DataCamp - Free intro level courses with intermediate to advanced level requiring paid subscription. RStudio/Shiny Webinars - All events are free, routinely updated, cover a variety of subjects and products including Open Source and Commercial. Material from the add-on module 'Statistical Inference' is similar to material covered in ISA 205, except you use R programming to learn the concepts. This webinar is for system administrators or. We’ll demo Connect for users who aren’t familiar, then you’ll learn about what systems we rely on, where things are stored, and the basics of managing the server. This is a great follow-up to TryR mentioned above and add-on modules can be installed (See Step 5 provided at the linked website). In this webinar we’ll provide an overview of how RStudio Connect works under the hood. Swirl - Free R package that can be downloaded and installed so that the user can learn R programming at their own pace using the R console. Other free Code School courses are also offered by the linked website as well as others with a paid subscription (Note: completion of the free course may provide you a discounted rate!) Requires no installation of software and is a great introduction to the R language and using R as a tool for statistics and data modeling. You can setup an online account with Code School, but is not necessary. Try R - Highly recommended for beginners.
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