Edited day2 file

README.md

@@ -1,5 +1,5 @@
 # Lectures on Quantitative Methods for ACJ Students
 
 ### [Day 1](../master/acjlecturesday1.org)
-### [Day 2](../master/acjlecturesday1.org)
+### [Day 2](../master/acjlecturesday2.org)
 

acjlecturesday2.org

@@ -43,99 +43,8 @@
 
 ** Sampling Distributions                                            :slide:
 
-#+RESULTS: sampling
+#+RESULTS: sampling2
-[[file:bsample.png]]
+[[file:bsample2.png]]
-
-#+NAME: sampling
-#+BEGIN_SRC R :results output graphics :exports results :file bsample.png :width 4500 :height 3000  :res 600
-    library(data.table)
-    readRDS("plfsdata/plfsacjdata.rds")->worker
-    worker$standardwage->worker$wage
-    #read.table("~/ssercloud/acj2018/worker.csv",sep=",",header=T)->worker
-    c(1:nrow(worker))->worker$SamplingFrameOrder
-    worker[sex!=3,]->worker
-    library(ggplot2)
-      ggplot(worker,aes(wage))+geom_density(colour="black",size=1)+scale_y_continuous(limits=c(0,0.05))+scale_x_continuous(limits=c(0,1000),breaks=c(0,mean(worker$wage),1000))->p
-  #    p+facet_wrap(~sex)->p
-    p+annotate("text",x=520,y=0.045,
-               label=paste("Population mean = ",round(mean(worker$wage)),sep=""))->p
-      p+theme_bw()->p
-      p
-
-
-
-    sample(1:nrow(worker),5, replace=FALSE)->a1
-    worker[a1,]->s1
-    mean(s1$wage)->t1
-    for (i in c(1:9999)) {
-        sample(1:nrow(worker),5, replace=FALSE)->a1
-        worker[a1,]->s1
-        c(t1,mean(s1$wage))->t1
-    }
-
-    data.frame(sno=c(1:10000),meancol=t1)->t1
-    p+geom_density(data=t1,aes(meancol),colour="blue",size=1)-> p
-    paste("Distribution of sample means (5): mean = ",
-          round(mean(t1$meancol)),
-          "; stdev = ",
-          round(sqrt(var(t1$meancol))),sep="")->lab
-    p+annotate("text",x=700,y=0.033,label=lab,colour="blue")->p
-    p
-
-    sample(1:nrow(worker),20, replace=FALSE)->a1
-    worker[a1,]->s1
-    mean(s1$wage)->t0
-    for (i in c(1:9999)) {
-        sample(1:nrow(worker),20, replace=FALSE)->a1
-        worker[a1,]->s1
-        c(t0,mean(s1$wage))->t0
-    }
-
-    data.frame(sno=c(1:10000),meancol=t0)->t0
-    p+geom_density(data=t0,aes(meancol),colour="darkolivegreen",size=1)-> p
-    paste("Distribution of sample means (20): mean = ",
-          round(mean(t0$meancol)),
-          "; stdev = ",
-          round(sqrt(var(t0$meancol))),sep="")->lab
-    p+annotate("text",x=700,y=0.036,label=lab,colour="darkolivegreen")->p
-    p
-
-    sample(1:nrow(worker),50, replace=FALSE)->a1
-    worker[a1,]->s1
-    mean(s1$wage)->t
-    for (i in c(1:9999)) {
-        sample(1:nrow(worker),50, replace=FALSE)->a1
-        worker[a1,]->s1
-        c(t,mean(s1$wage))->t
-    }
-
-    data.frame(sno=c(1:10000),meancol=t)->t
-    p+geom_density(data=t,aes(meancol),colour="red",size=1)-> p
-    paste("Distribution of sample means (50): mean = ",
-          round(mean(t$meancol)),
-          "; stdev = ",
-          round(sqrt(var(t$meancol))),sep="")->lab
-    p+annotate("text",x=700,y=0.039,label=lab,colour="red")->p
-    p
-
-    sample(1:nrow(worker),200, replace=FALSE)->a1
-    worker[a1,]->s1
-    mean(s1$wage)->t4
-    for (i in c(1:9999)) {
-      sample(1:nrow(worker),200, replace=FALSE)->a1
-      worker[a1,]->s1
-      c(t4,mean(s1$wage))->t4
-    }
-
-    data.frame(sno=c(1:10000),meancol=t4)->t4
-    p+geom_density(data=t4,aes(meancol),colour="pink",size=1)-> p
-    paste("Distribution of sample means (200): mean = ",
-          round(mean(t4$meancol)),
-          "; stdev = ",
-          round(sqrt(var(t4$meancol))),sep="")->lab
-    p+annotate("text",x=700,y=0.042,label=lab,colour="pink")->p
-    p
-#+end_src
 
 #+NAME: sampling2
 #+BEGIN_SRC R :results output graphics :exports results :file bsample2.png :width 4500 :height 3000  :res 600
@@ -230,7 +139,4 @@
     p
 #+end_src
 
-#+RESULTS: sampling2
-[[file:bsample2.png]]
-