Melissa Kline Struhl

🦇 Statistics teaching bat signal! 🦇

I started grad school exactly 2 years too late for a course I am still very jealous of that started with generating and visualizing distributions, moved on to bootstrapping and other sampling-based inference strategies, and then eventually wound up in the world of mixed effects models. Seemed to create comfort and confidence about reasoning w/ data, rather than memorizing the definition of a p value.

Are there OER for this? R-based, as long as I'm wishing for unicorns...

May 25, 2023 at 3:46pmWeb
Show threadCecilia NoeckerMay 25, 2023
@melissaekline Sounds somewhat similar to this course/textbook? https://bookdown.org/roback/bookdown-BeyondMLR/
Beyond Multiple Linear Regression

An applied textbook on generalized linear models and multilevel models for advanced undergraduates, featuring many real, unique data sets. It is intended to be accessible to undergraduate students who have successfully completed a regression course. Even though there is no mathematical prerequisite, we still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. We believe strongly in case studies featuring real data and real research questions; thus, most of the data in the textbook arises from collaborative research conducted by the authors and their students, or from student projects. Our goal is that, after working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling.

Show threadDr. Robert M FlightMay 25, 2023

@melissaekline I think this book by Rafael Irizarry and @mikelove goes through some of that kind of stuff, but it's been a while since I looked at it.

There is an option to have it for free from Leanpub as well.

https://leanpub.com/dataanalysisforthelifesciences

Data Analysis for the Life Sciences

Leanpub
Show threadHao YeMay 25, 2023

@melissaekline
https://seeing-theory.brown.edu/

https://psyteachr.github.io/

https://learningstatisticswithr.com/

I have often felt there is a bit of a spectrum from teaching data analysis in R (more focus on getting students comfortable manipulating data in R) and statistical theory (more emphasis on data generating process, digging into inference conceptually, with maybe implementation in R). I'm not sure from your description where that might fall. Sometimes the content does get split out over multiple courses!

Seeing Theory

A visual introduction to probability and statistics.

Show threadMelissa Kline StruhlMay 26, 2023
@hye Wow that seeing theory site is incredible! 🔥🔥🔥
Show threadMelissa Kline StruhlMay 26, 2023
@hye And more of the latter, I think - in this case, the R facility was a great bonus, but what impressed me was the fact that simulation methods could be the easy thing that set you up for clear intuitions about what statistical tests are telling you, rather than an advanced topic you don't touch until after you learn your ANOVA/t-test cookbook, was the thing that really impressed me
Show threadHao YeMay 26, 2023
@melissaekline Digging through some old tweets, I also re-discovered this https://www.bookdown.org/ybrandvain/Applied-Biostats/
Applied Biostats

Course notes for applied Biostats.

Show threadHao YeMay 26, 2023
@melissaekline One more https://lakens.github.io/statistical_inferences/
Improving Your Statistical Inferences

This open educational resource contains information to improve statistical inferences, design better experiments, and report scientific research more transparently.