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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 computationSun, 09 Dec 2012 10:53:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/09/t1355068480dh5rdhpz4lfklva.htm/, Retrieved Fri, 01 Nov 2024 00:32:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197942, Retrieved Fri, 01 Nov 2024 00:32:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP           [Histogram] [Histogram Aantal ...] [2012-12-09 15:53:30] [843149dd24ea3aaab20d8c5630e75083] [Current]
- RM D            [Notched Boxplots] [] [2012-12-09 16:23:30] [1fb2eba5b33bc8e02149c0fefc9df588]
- RM D            [Notched Boxplots] [] [2012-12-09 17:41:37] [1fb2eba5b33bc8e02149c0fefc9df588]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197942&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197942&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197942&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 time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[8400,8600[850020.0266670.0266670.000133
[8600,8800[870030.040.0666672e-04
[8800,9000[890020.0266670.0933330.000133
[9000,9200[9100100.1333330.2266670.000667
[9200,9400[930080.1066670.3333330.000533
[9400,9600[950090.120.4533336e-04
[9600,9800[9700170.2266670.680.001133
[9800,10000[990080.1066670.7866670.000533
[10000,10200[1010080.1066670.8933330.000533
[10200,10400[1030020.0266670.920.000133
[10400,10600[1050050.0666670.9866670.000333
[10600,10800]1070010.01333316.7e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[8400,8600[ & 8500 & 2 & 0.026667 & 0.026667 & 0.000133 \tabularnewline
[8600,8800[ & 8700 & 3 & 0.04 & 0.066667 & 2e-04 \tabularnewline
[8800,9000[ & 8900 & 2 & 0.026667 & 0.093333 & 0.000133 \tabularnewline
[9000,9200[ & 9100 & 10 & 0.133333 & 0.226667 & 0.000667 \tabularnewline
[9200,9400[ & 9300 & 8 & 0.106667 & 0.333333 & 0.000533 \tabularnewline
[9400,9600[ & 9500 & 9 & 0.12 & 0.453333 & 6e-04 \tabularnewline
[9600,9800[ & 9700 & 17 & 0.226667 & 0.68 & 0.001133 \tabularnewline
[9800,10000[ & 9900 & 8 & 0.106667 & 0.786667 & 0.000533 \tabularnewline
[10000,10200[ & 10100 & 8 & 0.106667 & 0.893333 & 0.000533 \tabularnewline
[10200,10400[ & 10300 & 2 & 0.026667 & 0.92 & 0.000133 \tabularnewline
[10400,10600[ & 10500 & 5 & 0.066667 & 0.986667 & 0.000333 \tabularnewline
[10600,10800] & 10700 & 1 & 0.013333 & 1 & 6.7e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197942&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][8400,8600[[/C][C]8500[/C][C]2[/C][C]0.026667[/C][C]0.026667[/C][C]0.000133[/C][/ROW]
[ROW][C][8600,8800[[/C][C]8700[/C][C]3[/C][C]0.04[/C][C]0.066667[/C][C]2e-04[/C][/ROW]
[ROW][C][8800,9000[[/C][C]8900[/C][C]2[/C][C]0.026667[/C][C]0.093333[/C][C]0.000133[/C][/ROW]
[ROW][C][9000,9200[[/C][C]9100[/C][C]10[/C][C]0.133333[/C][C]0.226667[/C][C]0.000667[/C][/ROW]
[ROW][C][9200,9400[[/C][C]9300[/C][C]8[/C][C]0.106667[/C][C]0.333333[/C][C]0.000533[/C][/ROW]
[ROW][C][9400,9600[[/C][C]9500[/C][C]9[/C][C]0.12[/C][C]0.453333[/C][C]6e-04[/C][/ROW]
[ROW][C][9600,9800[[/C][C]9700[/C][C]17[/C][C]0.226667[/C][C]0.68[/C][C]0.001133[/C][/ROW]
[ROW][C][9800,10000[[/C][C]9900[/C][C]8[/C][C]0.106667[/C][C]0.786667[/C][C]0.000533[/C][/ROW]
[ROW][C][10000,10200[[/C][C]10100[/C][C]8[/C][C]0.106667[/C][C]0.893333[/C][C]0.000533[/C][/ROW]
[ROW][C][10200,10400[[/C][C]10300[/C][C]2[/C][C]0.026667[/C][C]0.92[/C][C]0.000133[/C][/ROW]
[ROW][C][10400,10600[[/C][C]10500[/C][C]5[/C][C]0.066667[/C][C]0.986667[/C][C]0.000333[/C][/ROW]
[ROW][C][10600,10800][/C][C]10700[/C][C]1[/C][C]0.013333[/C][C]1[/C][C]6.7e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197942&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197942&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
[8400,8600[850020.0266670.0266670.000133
[8600,8800[870030.040.0666672e-04
[8800,9000[890020.0266670.0933330.000133
[9000,9200[9100100.1333330.2266670.000667
[9200,9400[930080.1066670.3333330.000533
[9400,9600[950090.120.4533336e-04
[9600,9800[9700170.2266670.680.001133
[9800,10000[990080.1066670.7866670.000533
[10000,10200[1010080.1066670.8933330.000533
[10200,10400[1030020.0266670.920.000133
[10400,10600[1050050.0666670.9866670.000333
[10600,10800]1070010.01333316.7e-05


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Interval/Ratio ;
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 {
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')
}