View sesamplesize1multiplechoice.Rnw
<<echo=FALSE, results=hide>>=
## DATA GENERATION
mean.val<-round(rnorm(1,mean=100,sd=10),digits=0)
sd.val<-round(abs(rnorm(1,mean=10,sd=10)),digits=0)
n<-round(abs(rnorm(1,mean=100,sd=10)),digits=0)+1
se1<-round(sd.val/sqrt(n),digits=3)
se2<-round(sd.val/sqrt(n^2),digits=3)
questions <- character(5)
View ExampleExamCode.R
## Load library:
library("exams")
## exam questions:
myexamlist<-list("pnorm1","sesamplesize1multiplechoice")
## output directory
## create new test dir if one does not exist:
files.list<-system("ls",intern=TRUE)
View pnorm1.Rnw
<<echo=FALSE, results=hide>>=
## DATA GENERATION
mean.val<-round(rnorm(1,mean=100,sd=100),digits=0)
sd.val<-round(rnorm(1,mean=100,sd=10),digits=0)
upper<-round(rnorm(1,mean=100,sd=100)+50,digits=0)
lower<-round(rnorm(1,mean=100,sd=100)-100,digits=0)
sol<-pnorm(upper,mean=abs(mean.val),sd=abs(sd.val))-pnorm(lower,mean=abs(mean.val),sd=abs(sd.val))
sol<-round(sol,digits=3)
View solutiontest.tex
\documentclass[10pt,a4paper]{article}
%% packages
\usepackage{a4wide,verbatim,Sweave,url}
%% new environments
\newenvironment{question}{\item \textbf{Problem}\newline}{}
\newenvironment{solution}{\textbf{Solution}\newline}{}
\newenvironment{answerlist}{\renewcommand{\labelenumi}{(\alph{enumi})}\begin{enumerate}}{\end{enumerate}}
View test.tex
\documentclass[10pt,a4paper]{article}
%% packages
\usepackage{a4wide,verbatim,Sweave,url}
%% new environments
\newenvironment{question}{\item}{}
\newenvironment{solution}{\comment}{\endcomment}
\newenvironment{answerlist}{\renewcommand{\labelenumi}{(\alph{enumi})}\begin{enumerate}}{\end{enumerate}}
View powerinflationindex
## true effect size:
D<-seq(1,250,by=1)
## SE from a study:
se<-46
## sample size
n<-37
## typical SD:
stddev<-se*sqrt(n)
## rejection value (absolute) under null:
View typesm
## probable effect size derived from past studies:
D<-15
## SE from the study of interest:
se<-46
stddev<-se*sqrt(37)
nsim<-10000
drep<-rep(NA,nsim)
for(i in 1:nsim){
drep[i]<-mean(rnorm(37,mean=D,sd=stddev))
}
View vincentgranville.txt
“He seems to have a solid stats background back in the day”
A lot of people claim a lot of things about themselves. I have met a lot of people who characterize themselves as “fluent in Japanese” (oddly, these are always Americans), where their actual on-the-ground fluency level is pretty laughable.
I couldn’t find any clear statements about what his educational background is. He says on his linkedin page: “Facultés universitaires ‘Notre-Dame de la Paix’ Ph.D., Statistics, Mathematics, Science, 1983 – 1993″, Then he lists two courses he did there, “Stochastic Geometry, Markov Processes.” I find it odd that a guy does a PhD somewhere, over 10 years, and lists two courses under that PhD.
Also, I searched for this mysterious uni I have never heard of: Facultés universitaires ‘Notre-Dame de la Paix.
I ended up at a weird Jesuits page in Belgium:
View ranking.Rnw
<<>>=
# n: no of operations
# x: no of deaths
# N: no of hospitals
dat<-list(n=c(47,211,810,148,196,360,119,207,97,
256,148,215),
x=c(0,8,46,9,13,24,8,14,8,29,18,31),
N=12)
cat("model
View recoveringcorrelationsV2.R
### R code from vignette source 'recoveringcorrelationsV2.Rnw'
###################################################
### code chunk number 1: recoveringcorrelationsV2.Rnw:98-156
###################################################
new.df <- function(cond1.rt=487, effect.size=123,
sdev=544,
sdev.int.subj=160, sdev.slp.subj=195,
rho.u=0.6,
nsubj=37,