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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 14 Dec 2016 20:07:17 +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/2016/Dec/14/t1481743008mcnouup4txtpqmp.htm/, Retrieved Fri, 03 May 2024 22:48:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299698, Retrieved Fri, 03 May 2024 22:48:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram N2541] [2016-12-14 19:07:17] [153c3207812fd13fe5ceee3276565119] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4070
4229.2
3775.2
3584.2
5248
4182.4
4119
4082.4
3639.8
4020.6
4089.6
4373.6
4143.2
4604
4336.4
3953.6
4591.6
4272.4
3911.2
3911.2
4306.2
4280.2
4270.6
4387.8
4282.8
4534
4400.6
4282.8
5135.8
4524
4875.6
4593.8
4447.8
4406.6
5148.2
6357.6
4503.2
4688.2
4682.2
5012.6
5505.4
4871.8
4909.6
5025.6
4946.8
4943.6
5712.4
6932.4
5201.8
5247
4873.6
4854.8
5626.4
4769.4
4713.2
4762.4
5333.2
4960.8
4708.8
5490
4650.4
4376
4397.2
4318.6
4207.4
4488.6
4520
4358.8
4142.4
4052.8
4413.4
4837.4
3882.6
4672
3790
3713.4
5199.2
4016.2
3849.2
3903.4
3901.2
3943.2
4209.8
4850.2
4256.6
4479.6
3914
3849.4
4768
3944
4002.2
3768
4330.8
4109
3983
5666.8
3783
3599
3796.8
3663.8
4572.8
3914.6
3604
3777.4
3848.6
4110.6
4500.6
4701.6
4026
4415.4
4200.8
4325.8
4991.8
4244.2
4146.2
4109.2

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299698&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299698&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299698&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[3500,4000[3750260.2241380.2241380.000448
[4000,4500[4250440.379310.6034480.000759
[4500,5000[4750300.2586210.8620690.000517
[5000,5500[5250100.0862070.9482760.000172
[5500,6000[575040.0344830.9827596.9e-05
[6000,6500[625010.0086210.9913791.7e-05
[6500,7000]675010.00862111.7e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[3500,4000[ & 3750 & 26 & 0.224138 & 0.224138 & 0.000448 \tabularnewline
[4000,4500[ & 4250 & 44 & 0.37931 & 0.603448 & 0.000759 \tabularnewline
[4500,5000[ & 4750 & 30 & 0.258621 & 0.862069 & 0.000517 \tabularnewline
[5000,5500[ & 5250 & 10 & 0.086207 & 0.948276 & 0.000172 \tabularnewline
[5500,6000[ & 5750 & 4 & 0.034483 & 0.982759 & 6.9e-05 \tabularnewline
[6000,6500[ & 6250 & 1 & 0.008621 & 0.991379 & 1.7e-05 \tabularnewline
[6500,7000] & 6750 & 1 & 0.008621 & 1 & 1.7e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299698&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][3500,4000[[/C][C]3750[/C][C]26[/C][C]0.224138[/C][C]0.224138[/C][C]0.000448[/C][/ROW]
[ROW][C][4000,4500[[/C][C]4250[/C][C]44[/C][C]0.37931[/C][C]0.603448[/C][C]0.000759[/C][/ROW]
[ROW][C][4500,5000[[/C][C]4750[/C][C]30[/C][C]0.258621[/C][C]0.862069[/C][C]0.000517[/C][/ROW]
[ROW][C][5000,5500[[/C][C]5250[/C][C]10[/C][C]0.086207[/C][C]0.948276[/C][C]0.000172[/C][/ROW]
[ROW][C][5500,6000[[/C][C]5750[/C][C]4[/C][C]0.034483[/C][C]0.982759[/C][C]6.9e-05[/C][/ROW]
[ROW][C][6000,6500[[/C][C]6250[/C][C]1[/C][C]0.008621[/C][C]0.991379[/C][C]1.7e-05[/C][/ROW]
[ROW][C][6500,7000][/C][C]6750[/C][C]1[/C][C]0.008621[/C][C]1[/C][C]1.7e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299698&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299698&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
[3500,4000[3750260.2241380.2241380.000448
[4000,4500[4250440.379310.6034480.000759
[4500,5000[4750300.2586210.8620690.000517
[5000,5500[5250100.0862070.9482760.000172
[5500,6000[575040.0344830.9827596.9e-05
[6000,6500[625010.0086210.9913791.7e-05
[6500,7000]675010.00862111.7e-05


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,'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')
}