Welcome to MBP intro stats 2019. This web-site contains the instructions for how to prepare for the course, and will be updated with all the slides as they become available.
You will need a laptop with R and RStudio installed for this course. There are multiple good instructions around the web for getting it installed - here’s a good one you can follow:
http://web.cs.ucla.edu/~gulzar/rstudio/
At the end of those instructions it hints at installing packages. Here are the ones you should install:
A quick way of doing that in R (or in the Console in RStudio) is by copying and pasting the following commands:
required_packages = c("tidyverse", "forcats", "knitr", "lme4", "rmarkdown",
"ggplot2", "xaringan", "ggridges")
install.packages(required_packages)You will also want the following files downloaded and somewhere handy on your computer:
(Depending on your browser you might need to right click and select “Download as”).
These articles are required reading, and will be discussed in more detail on Thursday (so make sure to have read them by then):
Why Most Published Research Findings Are False
Scientific Utopia: II. Restructuring Incentives and Practices to Promote Truth Over Publishability
Readings these articles for Thursday is not stricly required, but encouraged:
The garden of the forking paths
Believe it or not: how much can we rely on published data on potential drug targets?
Lastly, these text books make for good general resources, both for the course and thinking through data analysis afterwards:
An Introduction to Statistical Learning
Statistical rethinking - sadly this one is not available for free online, but is fantastic and worth getting.