Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 19 Aug 2013 10:27:31 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/19/t13769224731p34iixsh6by4h1.htm/, Retrieved Wed, 01 May 2024 23:32:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211212, Retrieved Wed, 01 May 2024 23:32:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJespers Eva
Estimated Impact146
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Tijdreeks B - Stap 2] [2013-08-19 14:27:31] [0d1085ed835696cdd537ad5fa07600ec] [Current]
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Dataseries X:
19570
18845
19932
15946
20657
20294
21744
22469
25006
21744
20657
25730
21744
16308
19207
14496
20294
16670
22106
19932
21019
23556
23194
27542
19932
16670
18482
13409
19207
14858
21019
19932
17758
25368
22831
26093
19570
18120
16308
13409
17758
15946
21744
21019
18120
24281
22469
28992
23194
14134
14134
14134
16670
16670
22469
20657
18482
23194
21382
30804
24281
14134
14858
12322
17033
19570
24643
24281
19570
22831
20294
28992
22106
17758
15946
11959
17758
21382
25006
23556
17395
25006
19570
30079
25006
18120
16670
11234
17758
17033
25730
25730
19570
25368
18845
29354
25006
18482
14134
9785
19207
18482
24281
27905
20657
23194
17395
30079




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211212&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211212&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211212&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[8000,10000[900010.0092590.0092595e-06
[10000,12000[1100020.0185190.0277789e-06
[12000,14000[1300030.0277780.0555561.4e-05
[14000,16000[15000110.1018520.1574075.1e-05
[16000,18000[17000160.1481480.3055567.4e-05
[18000,20000[19000220.2037040.5092590.000102
[20000,22000[21000160.1481480.6574077.4e-05
[22000,24000[23000130.120370.7777786e-05
[24000,26000[25000150.1388890.9166676.9e-05
[26000,28000[2700030.0277780.9444441.4e-05
[28000,30000[2900030.0277780.9722221.4e-05
[30000,32000]3100030.02777811.4e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[8000,10000[ & 9000 & 1 & 0.009259 & 0.009259 & 5e-06 \tabularnewline
[10000,12000[ & 11000 & 2 & 0.018519 & 0.027778 & 9e-06 \tabularnewline
[12000,14000[ & 13000 & 3 & 0.027778 & 0.055556 & 1.4e-05 \tabularnewline
[14000,16000[ & 15000 & 11 & 0.101852 & 0.157407 & 5.1e-05 \tabularnewline
[16000,18000[ & 17000 & 16 & 0.148148 & 0.305556 & 7.4e-05 \tabularnewline
[18000,20000[ & 19000 & 22 & 0.203704 & 0.509259 & 0.000102 \tabularnewline
[20000,22000[ & 21000 & 16 & 0.148148 & 0.657407 & 7.4e-05 \tabularnewline
[22000,24000[ & 23000 & 13 & 0.12037 & 0.777778 & 6e-05 \tabularnewline
[24000,26000[ & 25000 & 15 & 0.138889 & 0.916667 & 6.9e-05 \tabularnewline
[26000,28000[ & 27000 & 3 & 0.027778 & 0.944444 & 1.4e-05 \tabularnewline
[28000,30000[ & 29000 & 3 & 0.027778 & 0.972222 & 1.4e-05 \tabularnewline
[30000,32000] & 31000 & 3 & 0.027778 & 1 & 1.4e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211212&T=1

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][8000,10000[[/C][C]9000[/C][C]1[/C][C]0.009259[/C][C]0.009259[/C][C]5e-06[/C][/ROW]
[ROW][C][10000,12000[[/C][C]11000[/C][C]2[/C][C]0.018519[/C][C]0.027778[/C][C]9e-06[/C][/ROW]
[ROW][C][12000,14000[[/C][C]13000[/C][C]3[/C][C]0.027778[/C][C]0.055556[/C][C]1.4e-05[/C][/ROW]
[ROW][C][14000,16000[[/C][C]15000[/C][C]11[/C][C]0.101852[/C][C]0.157407[/C][C]5.1e-05[/C][/ROW]
[ROW][C][16000,18000[[/C][C]17000[/C][C]16[/C][C]0.148148[/C][C]0.305556[/C][C]7.4e-05[/C][/ROW]
[ROW][C][18000,20000[[/C][C]19000[/C][C]22[/C][C]0.203704[/C][C]0.509259[/C][C]0.000102[/C][/ROW]
[ROW][C][20000,22000[[/C][C]21000[/C][C]16[/C][C]0.148148[/C][C]0.657407[/C][C]7.4e-05[/C][/ROW]
[ROW][C][22000,24000[[/C][C]23000[/C][C]13[/C][C]0.12037[/C][C]0.777778[/C][C]6e-05[/C][/ROW]
[ROW][C][24000,26000[[/C][C]25000[/C][C]15[/C][C]0.138889[/C][C]0.916667[/C][C]6.9e-05[/C][/ROW]
[ROW][C][26000,28000[[/C][C]27000[/C][C]3[/C][C]0.027778[/C][C]0.944444[/C][C]1.4e-05[/C][/ROW]
[ROW][C][28000,30000[[/C][C]29000[/C][C]3[/C][C]0.027778[/C][C]0.972222[/C][C]1.4e-05[/C][/ROW]
[ROW][C][30000,32000][/C][C]31000[/C][C]3[/C][C]0.027778[/C][C]1[/C][C]1.4e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211212&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211212&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[8000,10000[900010.0092590.0092595e-06
[10000,12000[1100020.0185190.0277789e-06
[12000,14000[1300030.0277780.0555561.4e-05
[14000,16000[15000110.1018520.1574075.1e-05
[16000,18000[17000160.1481480.3055567.4e-05
[18000,20000[19000220.2037040.5092590.000102
[20000,22000[21000160.1481480.6574077.4e-05
[22000,24000[23000130.120370.7777786e-05
[24000,26000[25000150.1388890.9166676.9e-05
[26000,28000[2700030.0277780.9444441.4e-05
[28000,30000[2900030.0277780.9722221.4e-05
[30000,32000]3100030.02777811.4e-05



Parameters (Session):
par2 = yellow ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = yellow ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
if (par4 == 'Unknown') par1 <- as.numeric(par1)
if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1)
if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5)
if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5)
if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5)
if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5)
if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5)
if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5)
if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5)
if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5)
bitmap(file='test1.png')
if(is.numeric(x[1])) {
if (is.na(par1)) {
myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)
} else {
if (par1 < 0) par1 <- 3
if (par1 > 50) par1 <- 50
myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)
}
} else {
plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency')
}
dev.off()
if(is.numeric(x[1])) {
myhist
n <- length(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('histogram.htm','Frequency Table (Histogram)',''),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bins',header=TRUE)
a<-table.element(a,'Midpoint',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
a<-table.element(a,'Density',header=TRUE)
a<-table.row.end(a)
crf <- 0
if (par3 == FALSE) mybracket <- '[' else mybracket <- ']'
mynumrows <- (length(myhist$breaks)-1)
for (i in 1:mynumrows) {
a<-table.row.start(a)
if (i == 1)
dum <- paste('[',myhist$breaks[i],sep='')
else
dum <- paste(mybracket,myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- paste(dum,mybracket,sep='')
a<-table.element(a,dum,header=TRUE)
a<-table.element(a,myhist$mids[i])
a<-table.element(a,myhist$counts[i])
rf <- myhist$counts[i]/n
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
} else {
mytab
reltab <- mytab / sum(mytab)
n <- length(mytab)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Category',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,labels(mytab)$x[i],header=TRUE)
a<-table.element(a,mytab[i])
a<-table.element(a,round(reltab[i],4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}