master
Vikas Rawal 6 years ago
parent 5be831d0e9
commit f0aede0e12

@ -278,69 +278,3 @@
#+end_src
** Introduction to the t distribution :ignore:
#+RESULTS: sampling4
[[file:bsample4.png]]
#+NAME: sampling4
#+BEGIN_SRC R :results output graphics :exports results :file bsample4.png :width 2500 :height 2000 :res 300
library(data.table)
library(ggplot2)
options(scipen=9999)
readRDS("plfsdata/plfsacjdata.rds")->worker
worker$standardwage->worker$wage
c(1:nrow(worker))->worker$SamplingFrameOrder
worker[sex!=3,]->worker
worker->t9
(t9$wage-mean(t9$wage))/sqrt(var(t9$wage))->t9$wage
ggplot(t9,aes(wage))+geom_density(colour="black",size=1)->p
p+scale_y_continuous(limits=c(0,0.75))->p
p+scale_x_continuous(limits=c(-15,15)
,breaks=c(-15,0,round(mean(worker$wage)),15))->p
p+theme_bw()->p
p
data.frame(sno=c(),meancol=c(),sterr=c())->t4
samplesize=50
for (i in c(1:20000)) {
sample(1:nrow(worker),samplesize, replace=FALSE)->a1
worker[a1,]->s1
rbind(t4,data.frame(
sno=i,
meancol=mean(s1$wage),
sterr=sqrt(var(s1$wage))/sqrt(samplesize)))->t4
}
(t4$meancol-mean(t4$meancol))/t4$sterr->t4$teststat
(t4$meancol-mean(t4$meancol))/sqrt(var(t4$meancol))->t4$teststat2
data.frame(modelt=rt(20000,29))->m
var(t4$teststat)
var(m$modelt)
var(t4$teststat2)
ggplot()->p
p+geom_density(data=t4,aes(teststat),colour="blue",size=1)-> p
p+geom_density(data=m,aes(modelt),colour="darkolivegreen",size=1)->p
p+geom_density(data=t4,aes(teststat2),colour="red",size=1)-> p
p+annotate("text",x=3,y=0.4,
label=paste("Var of statistic with unknown variance:",
round(var(t4$teststat),2)),
colour="blue")->p
p+annotate("text",x=3,y=0.39,
label=paste("Var of statistic with known variance:",
round(var(t4$teststat2),2)),
colour="red")->p
p+annotate("text",x=3,y=0.38,
label=paste("Var of t-distribution:",round(var(m$modelt),2)),
colour="darkolivegreen")->p
p
#+end_src

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