Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 16 Aug 2015 16:06:26 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/16/t14397376342ss6n16axati96w.htm/, Retrieved Sat, 18 May 2024 20:23:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280166, Retrieved Sat, 18 May 2024 20:23:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2014-09-20 19:01:39] [46d78fa4bef23992fc20db72a2a0da97]
- RMPD    [Histogram] [] [2015-08-16 15:06:26] [fced41568b3cc41e6659ad201d611503] [Current]
- R         [Histogram] [] [2015-08-16 15:23:09] [46d78fa4bef23992fc20db72a2a0da97]
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Dataseries X:
95320.00
94965.00
94605.00
93860.00
101230.00
100840.00
95320.00
91650.00
92005.00
92005.00
92400.00
93110.00
94215.00
94215.00
93505.00
91650.00
101230.00
102690.00
100485.00
95320.00
97530.00
94215.00
95710.00
96425.00
97170.00
95320.00
95710.00
93110.00
101230.00
103795.00
101590.00
97530.00
101945.00
97170.00
101590.00
101230.00
102335.00
98275.00
102690.00
102335.00
108960.00
107465.00
101590.00
98630.00
102690.00
97170.00
101230.00
101945.00
103440.00
100130.00
101945.00
103050.00
107110.00
103795.00
99380.00
94605.00
99025.00
86875.00
92755.00
96065.00
99380.00
94605.00
94605.00
94605.00
97170.00
93505.00
88695.00
84670.00
87590.00
76190.00
83175.00
87235.00
87980.00
83920.00
84275.00
83175.00
86875.00
84275.00
79150.00
75445.00
81710.00
68105.00
76940.00
80965.00
80965.00
76190.00
71775.00
71420.00
75445.00
71775.00
64795.00
59985.00
65150.00
53005.00
64045.00
69920.00
71775.00
67715.00
62585.00
66255.00
67715.00
66610.00
55565.00
50440.00
54105.00
43065.00
54465.00
58525.00
61835.00
56315.00
51150.00
54105.00
55565.00
52645.00
41605.00
36795.00
41210.00
29065.00
42315.00
50440.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280166&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280166&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280166&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20000,30000[2500010.0083330.0083331e-06
[30000,40000[3500010.0083330.0166671e-06
[40000,50000[4500040.0333330.053e-06
[50000,60000[55000130.1083330.1583331.1e-05
[60000,70000[65000110.0916670.259e-06
[70000,80000[75000100.0833330.3333338e-06
[80000,90000[85000150.1250.4583331.2e-05
[90000,1e+05[95000390.3250.7833333.2e-05
[1e+05,110000]105000260.21666712.2e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20000,30000[ & 25000 & 1 & 0.008333 & 0.008333 & 1e-06 \tabularnewline
[30000,40000[ & 35000 & 1 & 0.008333 & 0.016667 & 1e-06 \tabularnewline
[40000,50000[ & 45000 & 4 & 0.033333 & 0.05 & 3e-06 \tabularnewline
[50000,60000[ & 55000 & 13 & 0.108333 & 0.158333 & 1.1e-05 \tabularnewline
[60000,70000[ & 65000 & 11 & 0.091667 & 0.25 & 9e-06 \tabularnewline
[70000,80000[ & 75000 & 10 & 0.083333 & 0.333333 & 8e-06 \tabularnewline
[80000,90000[ & 85000 & 15 & 0.125 & 0.458333 & 1.2e-05 \tabularnewline
[90000,1e+05[ & 95000 & 39 & 0.325 & 0.783333 & 3.2e-05 \tabularnewline
[1e+05,110000] & 105000 & 26 & 0.216667 & 1 & 2.2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280166&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][20000,30000[[/C][C]25000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]1e-06[/C][/ROW]
[ROW][C][30000,40000[[/C][C]35000[/C][C]1[/C][C]0.008333[/C][C]0.016667[/C][C]1e-06[/C][/ROW]
[ROW][C][40000,50000[[/C][C]45000[/C][C]4[/C][C]0.033333[/C][C]0.05[/C][C]3e-06[/C][/ROW]
[ROW][C][50000,60000[[/C][C]55000[/C][C]13[/C][C]0.108333[/C][C]0.158333[/C][C]1.1e-05[/C][/ROW]
[ROW][C][60000,70000[[/C][C]65000[/C][C]11[/C][C]0.091667[/C][C]0.25[/C][C]9e-06[/C][/ROW]
[ROW][C][70000,80000[[/C][C]75000[/C][C]10[/C][C]0.083333[/C][C]0.333333[/C][C]8e-06[/C][/ROW]
[ROW][C][80000,90000[[/C][C]85000[/C][C]15[/C][C]0.125[/C][C]0.458333[/C][C]1.2e-05[/C][/ROW]
[ROW][C][90000,1e+05[[/C][C]95000[/C][C]39[/C][C]0.325[/C][C]0.783333[/C][C]3.2e-05[/C][/ROW]
[ROW][C][1e+05,110000][/C][C]105000[/C][C]26[/C][C]0.216667[/C][C]1[/C][C]2.2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280166&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280166&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
[20000,30000[2500010.0083330.0083331e-06
[30000,40000[3500010.0083330.0166671e-06
[40000,50000[4500040.0333330.053e-06
[50000,60000[55000130.1083330.1583331.1e-05
[60000,70000[65000110.0916670.259e-06
[70000,80000[75000100.0833330.3333338e-06
[80000,90000[85000150.1250.4583331.2e-05
[90000,1e+05[95000390.3250.7833333.2e-05
[1e+05,110000]105000260.21666712.2e-05



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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}