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My textbook with Kosuke Imai (@Harvard) is finally out!
Assuming no prior knowledge of statistics or coding and only minimal knowledge of math, DSS teaches the fundamentals of survey research, predictive models, and causal inference + how to analyze real-world data with R.
🧵..
Assuming no prior knowledge of statistics or coding and only minimal knowledge of math, DSS teaches the fundamentals of survey research, predictive models, and causal inference + how to analyze real-world data with R.
🧵..
1/n: DSS is meant for complete beginners, regardless of whether they are in high school, in graduate school, or out of school altogether. #rstats #surveys #prediction #causality
Want to see for yourself? The first chapter is free here: bit.ly/dss_preview
Book outline:
Want to see for yourself? The first chapter is free here: bit.ly/dss_preview
Book outline:
2/n: We wrote DSS so that anyone could learn the skills we teach by following along with the exercises in the book on their own computer, without the help of an instructor. (Everything needed is either in the book or on the book's website.) #rstats #surveys #prediction #causality
Here's a basic tutorial for how to do simple linear regression in R!
(all in one thread?!)
#regression #Rstats #datascience #tutorial #ecology #Rthread #linearmodel #dataanalysis #statistics
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(all in one thread?!)
#regression #Rstats #datascience #tutorial #ecology #Rthread #linearmodel #dataanalysis #statistics
[1/15]
First we are going to load some data. Let's use the built-in "trees" dataset by running:
data(trees)
This dataset is based on 31 black cherry trees trunks: their diameter at breast height (DBH) in inches (girth), height in feet, and wood volume in cubic feet.
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data(trees)
This dataset is based on 31 black cherry trees trunks: their diameter at breast height (DBH) in inches (girth), height in feet, and wood volume in cubic feet.
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Let's first rename the columns for clarity:
names(trees) <- c("DBH_in","height_ft", "volume_ft3")
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names(trees) <- c("DBH_in","height_ft", "volume_ft3")
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