This is a recording of American University's Statistics 412/612 course on Introduction to R Programming. You can find the material from this meeting here: american-stat-...
Actually, I have never left a comment on RU-vid but after going through this video and how you explained function syntax~ , girl I couldn't stop myself from telling you that you are good. Thank you.
Thanks Ms. Gonzalez! This is exactly the way an intro to R course should be taught. The sad reality is most people majoring in statistics or data science unfortunately WILL NOT have the chance to be cross-trained as software engineers and merely need to know how to wrangle the data to get it into a "model ready" format (since modeling tends to be the easier part of the analysis once the data is preprocessed correctly). If my old professors had taught R this way life would've been so much easier. Instead I was given links to sites or texts that either treated you like an idiot with the most basic examples or read like a reference manual. This is exactly what turns a lot of people away from R. I especially enjoyed the following: - Ms. Gonzalez uses interactive coding sessions where she prompts the students to help finish lines and checks understanding - Focused on up-to-date software (tidyverse / dplyr in this case) instead of relying solely on base R - Multiple use cases of functions were shown to help students understand nuance and detail Great work!
This is wonderful feedback, thank you! I'm glad it helped you. I follow the coding pedagogy of Software Carpentries, so thanks to the countless people who have researched how to teach coding well that in turn taught me.
Kelsey, Awesome tutorial. df%>%summarise(across(everything(), ~ is.na(.x), useful to display all rows with missing values and investigate the pattern or the missiness and decide what to do with them.
I just discovered your RU-vid channel. It's amazing. Please keep up the great work. And I wish if you do a tutorial on inferential statistics with R. Thanks in advance.
Hi Sahil - I'm glad you enjoyed it. Here are some practice questions you can use! Basic data wrangling: american-stat-412612.netlify.app/assignment/03-lab/ Advanced data wrangling: american-stat-412612.netlify.app/assignment/05-lab/
@@KelseyCodes Could you do a video on Meta-Programming, if possible? I recently discovered the new operators, curly-curly, walrus, & bang-bang-bang. Not only did I find them useful, but they also made my code so elegant & pretty. I would be thrilled if you did a deep dive on them. Thanks again for your lovely videos.
