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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, 21 Dec 2016 11:28:05 +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/21/t1482316210bkfi7r7g2p7xrd5.htm/, Retrieved Tue, 07 May 2024 03:53:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302068, Retrieved Tue, 07 May 2024 03:53:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histrogram] [2016-12-21 10:28:05] [4b9ab307db0841e06829391b8f16ae7f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4998
4480
4824
4814
4602
4499
4594
4600
4507
4606
4503
4801
4564
4142
4818
4408
4496
4587
4656
4799
4652
4638
4650
5185
5208
4477
4976
4670
4842
4713
4804
4996
4574
4841
4688
4766
4994
4514
4766
4642
4806
4645
4784
4979
4530
4942
4651
5150
4987
4532
5046
4783
4958
4815
5055
5152
4773
5147
4866
5311
5172
4734
5011
4957
4968
5049
5305
5067
5001
5252
4903
5408
5395
5150
5460
4968
5021
5118
5175
5420
5121
5450
5286
5693
5353
5017
5577
4987
5129
5249
5100
5382
5039
5364
5193
5846
5259
4809
5297
5034
5243
5150
5296
5596
4954
5250
5009
5113
5237
4575
5026
4842
5019
5063
5261
5327
5054
5269
5019
5315
5274
4899
5216
5029
5110
5093

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302068&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302068&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302068&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 time1 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[4000,4200[410010.0079370.0079374e-05
[4200,4400[4300000.0079370
[4400,4600[4500150.1190480.1269840.000595
[4600,4800[4700200.158730.2857140.000794
[4800,5000[4900270.2142860.50.001071
[5000,5200[5100330.2619050.7619050.00131
[5200,5400[5300220.1746030.9365080.000873
[5400,5600[550060.0476190.9841270.000238
[5600,5800[570010.0079370.9920634e-05
[5800,6000]590010.00793714e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4000,4200[ & 4100 & 1 & 0.007937 & 0.007937 & 4e-05 \tabularnewline
[4200,4400[ & 4300 & 0 & 0 & 0.007937 & 0 \tabularnewline
[4400,4600[ & 4500 & 15 & 0.119048 & 0.126984 & 0.000595 \tabularnewline
[4600,4800[ & 4700 & 20 & 0.15873 & 0.285714 & 0.000794 \tabularnewline
[4800,5000[ & 4900 & 27 & 0.214286 & 0.5 & 0.001071 \tabularnewline
[5000,5200[ & 5100 & 33 & 0.261905 & 0.761905 & 0.00131 \tabularnewline
[5200,5400[ & 5300 & 22 & 0.174603 & 0.936508 & 0.000873 \tabularnewline
[5400,5600[ & 5500 & 6 & 0.047619 & 0.984127 & 0.000238 \tabularnewline
[5600,5800[ & 5700 & 1 & 0.007937 & 0.992063 & 4e-05 \tabularnewline
[5800,6000] & 5900 & 1 & 0.007937 & 1 & 4e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302068&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][4000,4200[[/C][C]4100[/C][C]1[/C][C]0.007937[/C][C]0.007937[/C][C]4e-05[/C][/ROW]
[ROW][C][4200,4400[[/C][C]4300[/C][C]0[/C][C]0[/C][C]0.007937[/C][C]0[/C][/ROW]
[ROW][C][4400,4600[[/C][C]4500[/C][C]15[/C][C]0.119048[/C][C]0.126984[/C][C]0.000595[/C][/ROW]
[ROW][C][4600,4800[[/C][C]4700[/C][C]20[/C][C]0.15873[/C][C]0.285714[/C][C]0.000794[/C][/ROW]
[ROW][C][4800,5000[[/C][C]4900[/C][C]27[/C][C]0.214286[/C][C]0.5[/C][C]0.001071[/C][/ROW]
[ROW][C][5000,5200[[/C][C]5100[/C][C]33[/C][C]0.261905[/C][C]0.761905[/C][C]0.00131[/C][/ROW]
[ROW][C][5200,5400[[/C][C]5300[/C][C]22[/C][C]0.174603[/C][C]0.936508[/C][C]0.000873[/C][/ROW]
[ROW][C][5400,5600[[/C][C]5500[/C][C]6[/C][C]0.047619[/C][C]0.984127[/C][C]0.000238[/C][/ROW]
[ROW][C][5600,5800[[/C][C]5700[/C][C]1[/C][C]0.007937[/C][C]0.992063[/C][C]4e-05[/C][/ROW]
[ROW][C][5800,6000][/C][C]5900[/C][C]1[/C][C]0.007937[/C][C]1[/C][C]4e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302068&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302068&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
[4000,4200[410010.0079370.0079374e-05
[4200,4400[4300000.0079370
[4400,4600[4500150.1190480.1269840.000595
[4600,4800[4700200.158730.2857140.000794
[4800,5000[4900270.2142860.50.001071
[5000,5200[5100330.2619050.7619050.00131
[5200,5400[5300220.1746030.9365080.000873
[5400,5600[550060.0476190.9841270.000238
[5600,5800[570010.0079370.9920634e-05
[5800,6000]590010.00793714e-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')
}