dgrapov

InChI=1S/C7H6O4/c8-5-3-1-2-4(6(5)9)7(10)11/h1-3,8-9H,(H,10,11)
InChI=1S/C7H12O5/c1-3(2)4(6(9)10)5(8)7(11)12/h3-5,8H,1-2H3,(H,9,10)(H,11,12)
InChI=1S/C3H4O5/c4-1(2(5)6)3(7)8/h1,4H,(H,5,6)(H,7,8)
InChI=1S/C5H8O3/c1-3(2)4(6)5(7)8/h3H,1-2H3,(H,7,8)
InChI=1S/C5H6O5/c6-3(5(9)10)1-2-4(7)8/h1-2H2,(H,7,8)(H,9,10)
InChI=1S/C4H6O3/c1-2-3(5)4(6)7/h2H2,1H3,(H,6,7)
InChI=1S/C6H10O3/c1-4(2)3-5(7)6(8)9/h4H,3H2,1-2H3,(H,8,9)
InChI=1S/C6H8O5/c7-4(6(10)11)2-1-3-5(8)9/h1-3H2,(H,8,9)(H,10,11)
InChI=1S/C7H6O4/c8-5-2-1-4(7(10)11)3-6(5)9/h1-3,8-9H,(H,10,11)
InChI=1S/C19H28O2/c1-18-9-7-13(20)11-12(18)3-4-14-15-5-6-17(21)19(15,2)10-8-16(14)18/h3,13-16,20H,4-11H2,1-2H3

dgrapov

19  GLDQAMYCGOIJDV-UHFFFAOYSA-N
36	RNQHMTFBUSSBJQ-UHFFFAOYSA-N
45	ROBFUDYVXSDBQM-UHFFFAOYSA-N
49	QHKABHOOEWYVLI-UHFFFAOYSA-N
51	KPGXRSRHYNQIFN-UHFFFAOYSA-N
58	TYEYBOSBBBHJIV-UHFFFAOYSA-N
70	BKAJNAXTPSGJCU-UHFFFAOYSA-N
71	FGSBNBBHOZHUBO-UHFFFAOYSA-N
72	YQUVCSBJEUQKSH-UHFFFAOYSA-N
76	FMGSKLZLMKYGDP-UHFFFAOYSA-N

dgrapov

C00005  C00006
C00003	C00004
C00002	C00008
C00019	C00021
C00007	C00027
C00010	C00024
C00002	C00020
C00002	C00013
C00002	C00009
C00015	C00029

dgrapov

689043	 C01197
6443013	 C14762
6443013	 C14762
6446027	 C14765
6446027	 C14765
11954058	 C14813
6439873	 C16326
6439873	 C16326
1004	C00009
1023	C00013

dgrapov

#load devium (or any other package) from github repo
source.git.hub<-function(url = "https://github.com/dgrapov/devium/tree/master/R")
 {
		 if(require(RCurl)==FALSE){install.packages("RCurl");library(RCurl)} else { library(RCurl)}
		 
		#get the names of all scripts to source
		obj<-getURL("https://github.com/dgrapov/devium/tree/master/R",ssl.verifypeer=FALSE)
		tmp<-strsplit(obj,'href=\"/')
		tmp2<-unlist(strsplit(as.character(unlist(tmp)),'class'))
		scripts<-gsub("/blob","",gsub('\" ',"",tmp2[grep("dgrapov/devium/blob/master/R/",tmp2)])) # fix formatting

dgrapov

#purpose: model the relationship between effects size, sample size and power 
# holding the significance level constant (p = 0.05) for three of the most common statistical tests:
# 1) t-Test (two-sample)

# then visualize the results for medium small, medium and large effect sizes (0.2,0.5,0.8 ; http://www.uccs.edu/lbecker/effect-size.html)

#Need pwr package
if(!require(pwr)){install.packages("pwr");library("pwr")}

# t-TEST

dgrapov

#test
test<-function(){print("hello world!")}