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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 computationMon, 05 Dec 2016 17:32:25 +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/05/t1480955565s73b4p2kq6z6kyd.htm/, Retrieved Wed, 01 May 2024 22:59:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297741, Retrieved Wed, 01 May 2024 22:59:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

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] [F1:N2774] [2016-12-03 13:43:19] [a4c5732063e280fade3b47e7f5057d96]
- RMPD    [Histogram] [F1:1809] [2016-12-05 16:32:25] [8d7b5e4c30a3b8052caee801f90adcea] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3650
3530
3800
4130
3440
4000
3690
4210
4240
4260
4510
4260
3420
3660
3790
3270
3250
3570
3410
4270
4410
4450
3990
4000
4140
3800
3060
3270
3040
3750
3330
3840
4060
3830
3880
3820
3640
2880
3710
2980
3190
3090
3190
3410
3310
3480
3750
3200
3150
3250
3290
2900
2940
3460
3890
3040
3000
3520
2850
2730
2820
3240
3160
3010
2720
2650
2790
3090
3240
3690
3490
2790
3060
3210
3080
2640
2890
3330
2970
2870
3140
3150
2940
2910
3060
2900
2980
2890
2920
2940
3300
3050
2740
3080
3090
2830
3390
3210
2970
2810
2690
2800
2920
2870
2860
3090
3180
3090

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=297741&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=297741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297741&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
[2600,2800[270080.0740740.0740740.00037
[2800,3000[2900230.2129630.2870370.001065
[3000,3200[3100220.2037040.4907410.001019
[3200,3400[3300150.1388890.629630.000694
[3400,3600[3500100.0925930.7222220.000463
[3600,3800[370090.0833330.8055560.000417
[3800,4000[390080.0740740.879630.00037
[4000,4200[410050.0462960.9259260.000231
[4200,4400[430050.0462960.9722220.000231
[4400,4600]450030.02777810.000139

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2600,2800[ & 2700 & 8 & 0.074074 & 0.074074 & 0.00037 \tabularnewline
[2800,3000[ & 2900 & 23 & 0.212963 & 0.287037 & 0.001065 \tabularnewline
[3000,3200[ & 3100 & 22 & 0.203704 & 0.490741 & 0.001019 \tabularnewline
[3200,3400[ & 3300 & 15 & 0.138889 & 0.62963 & 0.000694 \tabularnewline
[3400,3600[ & 3500 & 10 & 0.092593 & 0.722222 & 0.000463 \tabularnewline
[3600,3800[ & 3700 & 9 & 0.083333 & 0.805556 & 0.000417 \tabularnewline
[3800,4000[ & 3900 & 8 & 0.074074 & 0.87963 & 0.00037 \tabularnewline
[4000,4200[ & 4100 & 5 & 0.046296 & 0.925926 & 0.000231 \tabularnewline
[4200,4400[ & 4300 & 5 & 0.046296 & 0.972222 & 0.000231 \tabularnewline
[4400,4600] & 4500 & 3 & 0.027778 & 1 & 0.000139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297741&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][2600,2800[[/C][C]2700[/C][C]8[/C][C]0.074074[/C][C]0.074074[/C][C]0.00037[/C][/ROW]
[ROW][C][2800,3000[[/C][C]2900[/C][C]23[/C][C]0.212963[/C][C]0.287037[/C][C]0.001065[/C][/ROW]
[ROW][C][3000,3200[[/C][C]3100[/C][C]22[/C][C]0.203704[/C][C]0.490741[/C][C]0.001019[/C][/ROW]
[ROW][C][3200,3400[[/C][C]3300[/C][C]15[/C][C]0.138889[/C][C]0.62963[/C][C]0.000694[/C][/ROW]
[ROW][C][3400,3600[[/C][C]3500[/C][C]10[/C][C]0.092593[/C][C]0.722222[/C][C]0.000463[/C][/ROW]
[ROW][C][3600,3800[[/C][C]3700[/C][C]9[/C][C]0.083333[/C][C]0.805556[/C][C]0.000417[/C][/ROW]
[ROW][C][3800,4000[[/C][C]3900[/C][C]8[/C][C]0.074074[/C][C]0.87963[/C][C]0.00037[/C][/ROW]
[ROW][C][4000,4200[[/C][C]4100[/C][C]5[/C][C]0.046296[/C][C]0.925926[/C][C]0.000231[/C][/ROW]
[ROW][C][4200,4400[[/C][C]4300[/C][C]5[/C][C]0.046296[/C][C]0.972222[/C][C]0.000231[/C][/ROW]
[ROW][C][4400,4600][/C][C]4500[/C][C]3[/C][C]0.027778[/C][C]1[/C][C]0.000139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297741&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
[2600,2800[270080.0740740.0740740.00037
[2800,3000[2900230.2129630.2870370.001065
[3000,3200[3100220.2037040.4907410.001019
[3200,3400[3300150.1388890.629630.000694
[3400,3600[3500100.0925930.7222220.000463
[3600,3800[370090.0833330.8055560.000417
[3800,4000[390080.0740740.879630.00037
[4000,4200[410050.0462960.9259260.000231
[4200,4400[430050.0462960.9722220.000231
[4400,4600]450030.02777810.000139


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = additive ; par4 = 12 ;
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')
}