Comments (1)
- generate a bootstrapped sample by collecting a slope estimate from each student.
- each student does
library(dplyr)
new_cars = sample_n(cars, size = nrow(cars), replace = TRUE)
b1 = coef(lm(speed ~ dist, new_cars))[2]
- collect values somehow. google sheets?
- make each student do it 5 times
- then draw histogram of all collected b1's
boostrap
library(bootstrap)
fc = function(d,i){
d2 = d[i, ]
return(coef(lm(speed ~ dist,data = d2))[2])
}
bootcars <- boot(cars, fc, R=500)
plot(bootcars)
relate to testing against zero
from scpoeconometrics.
Related Issues (20)
- other useful lecture notes HOT 2
- write solutions for atlas project HOT 1
- case study 1: nate silver flights HOT 1
- chapter 2 tutorial update
- case studies and projects HOT 1
- interactions ch 4
- new app or section in dummy chapter
- need quiz for chapter2 tutorial
- remove airline dataset - too big HOT 1
- remove stargazer and go to huxreg
- fix bug in table log-log
- typo in log-level reg table
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- split apps from book
- change causality lecture
- we never define condition mean HOT 1
- Correlation
- nice book
- Typo in 07-Causality.Rmd
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