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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 01 Mar 2016 16:39:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/01/t14568503932z6pnjzqu18tbdk.htm/, Retrieved Tue, 07 May 2024 23:55:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293180, Retrieved Tue, 07 May 2024 23:55:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [verkoop aantal pe...] [2016-03-01 16:28:23] [4c392b130fccc63297597dd6ffb6df17]
- RMP     [Histogram] [aantal verkochte ...] [2016-03-01 16:39:06] [d7adcc7732e5b057da1b42af54844e1a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
68733
41381
51310
39036
42157
52574
39168
41325
40645
42303
38167
8980
66356
50335
47212
42247
45793
48248
40074
39602
41283
41900
29812
7236
56184
33958
34532
30277
30850
35492
33544
27829
33663
35690
27356
8033
62798
37581
44753
37546
36830
50683
38487
36522
45544
43575
36921
11393
74787
49019
56601
47637
49806
50499
42092
39062
44382
43635
41082
17244
70170
43949
52333
41032
47758
76116
30917
32996
31951
26775
30268
18214
47957
31901
35559
30408
30083
35043
30475
28309
31394
36313
40357
38918
44368
33298
29366
28282
30943
32699
29764
25524
29807
35112
32192
36214

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293180&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293180&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293180&T=0

As an alternative you can also use a QR Code:  
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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,10000[500030.031250.031253e-06
[10000,20000[1500030.031250.06253e-06
[20000,30000[25000100.1041670.1666671e-05
[30000,40000[35000380.3958330.56254e-05
[40000,50000[45000280.2916670.8541672.9e-05
[50000,60000[5500080.0833330.93758e-06
[60000,70000[6500030.031250.968753e-06
[70000,80000]7500030.0312513e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,10000[ & 5000 & 3 & 0.03125 & 0.03125 & 3e-06 \tabularnewline
[10000,20000[ & 15000 & 3 & 0.03125 & 0.0625 & 3e-06 \tabularnewline
[20000,30000[ & 25000 & 10 & 0.104167 & 0.166667 & 1e-05 \tabularnewline
[30000,40000[ & 35000 & 38 & 0.395833 & 0.5625 & 4e-05 \tabularnewline
[40000,50000[ & 45000 & 28 & 0.291667 & 0.854167 & 2.9e-05 \tabularnewline
[50000,60000[ & 55000 & 8 & 0.083333 & 0.9375 & 8e-06 \tabularnewline
[60000,70000[ & 65000 & 3 & 0.03125 & 0.96875 & 3e-06 \tabularnewline
[70000,80000] & 75000 & 3 & 0.03125 & 1 & 3e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293180&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][0,10000[[/C][C]5000[/C][C]3[/C][C]0.03125[/C][C]0.03125[/C][C]3e-06[/C][/ROW]
[ROW][C][10000,20000[[/C][C]15000[/C][C]3[/C][C]0.03125[/C][C]0.0625[/C][C]3e-06[/C][/ROW]
[ROW][C][20000,30000[[/C][C]25000[/C][C]10[/C][C]0.104167[/C][C]0.166667[/C][C]1e-05[/C][/ROW]
[ROW][C][30000,40000[[/C][C]35000[/C][C]38[/C][C]0.395833[/C][C]0.5625[/C][C]4e-05[/C][/ROW]
[ROW][C][40000,50000[[/C][C]45000[/C][C]28[/C][C]0.291667[/C][C]0.854167[/C][C]2.9e-05[/C][/ROW]
[ROW][C][50000,60000[[/C][C]55000[/C][C]8[/C][C]0.083333[/C][C]0.9375[/C][C]8e-06[/C][/ROW]
[ROW][C][60000,70000[[/C][C]65000[/C][C]3[/C][C]0.03125[/C][C]0.96875[/C][C]3e-06[/C][/ROW]
[ROW][C][70000,80000][/C][C]75000[/C][C]3[/C][C]0.03125[/C][C]1[/C][C]3e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293180&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293180&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,10000[500030.031250.031253e-06
[10000,20000[1500030.031250.06253e-06
[20000,30000[25000100.1041670.1666671e-05
[30000,40000[35000380.3958330.56254e-05
[40000,50000[45000280.2916670.8541672.9e-05
[50000,60000[5500080.0833330.93758e-06
[60000,70000[6500030.031250.968753e-06
[70000,80000]7500030.0312513e-06


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = grey ; 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 {
barplot(mytab <- sort(table(x),T),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')
}