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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 computationTue, 13 Dec 2016 08:52:43 +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/13/t1481615616f2o29yp6s1fho5h.htm/, Retrieved Fri, 01 Nov 2024 03:48:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299011, Retrieved Fri, 01 Nov 2024 03:48:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram N2031] [2016-12-13 07:52:43] [7b02c9ca65294818d9c418453f92ae83] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2870
2690
2790
2650
3500
2690
2790
2900
2690
3110
3020
3220
2860
3090
3240
2830
4060
3080
3120
3270
2740
3190
3220
3050
3180
2850
3920
2690
3270
2790
2500
2930
2630
2590
2710
2940
3230
3140
3140
2600
3520
3090
2760
2840
2310
3440
2790
2380
2210
2730
2590
2580
2670
2490
2570
3020
4840
2590
3240
2320
2590
2330
2880
2620
3220
3130
2790
3090
2910
3770
3220
2950
2930
3710
2920
3000
3360
3210
3100
3460
3300
3060
3730
3620
2800
3300
4020
3000
3350
3440
3430
3470
2920
3170
3510
3040
3320
2980
1180
3010
3780
3220
3590
3670
3270
3260
4170
2580
3960
3440
4160
3320
3510
3440
3620
3320
4840
3400
3700
3740
3450
3760
4050
3760
3700
3650

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=299011&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=299011&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299011&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
[1000,1500[125010.0079370.0079371.6e-05
[1500,2000[1750000.0079370
[2000,2500[225060.0476190.0555569.5e-05
[2500,3000[2750420.3333330.3888890.000667
[3000,3500[3250500.3968250.7857140.000794
[3500,4000[3750200.158730.9444440.000317
[4000,4500[425050.0396830.9841277.9e-05
[4500,5000]475020.01587313.2e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1000,1500[ & 1250 & 1 & 0.007937 & 0.007937 & 1.6e-05 \tabularnewline
[1500,2000[ & 1750 & 0 & 0 & 0.007937 & 0 \tabularnewline
[2000,2500[ & 2250 & 6 & 0.047619 & 0.055556 & 9.5e-05 \tabularnewline
[2500,3000[ & 2750 & 42 & 0.333333 & 0.388889 & 0.000667 \tabularnewline
[3000,3500[ & 3250 & 50 & 0.396825 & 0.785714 & 0.000794 \tabularnewline
[3500,4000[ & 3750 & 20 & 0.15873 & 0.944444 & 0.000317 \tabularnewline
[4000,4500[ & 4250 & 5 & 0.039683 & 0.984127 & 7.9e-05 \tabularnewline
[4500,5000] & 4750 & 2 & 0.015873 & 1 & 3.2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299011&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][1000,1500[[/C][C]1250[/C][C]1[/C][C]0.007937[/C][C]0.007937[/C][C]1.6e-05[/C][/ROW]
[ROW][C][1500,2000[[/C][C]1750[/C][C]0[/C][C]0[/C][C]0.007937[/C][C]0[/C][/ROW]
[ROW][C][2000,2500[[/C][C]2250[/C][C]6[/C][C]0.047619[/C][C]0.055556[/C][C]9.5e-05[/C][/ROW]
[ROW][C][2500,3000[[/C][C]2750[/C][C]42[/C][C]0.333333[/C][C]0.388889[/C][C]0.000667[/C][/ROW]
[ROW][C][3000,3500[[/C][C]3250[/C][C]50[/C][C]0.396825[/C][C]0.785714[/C][C]0.000794[/C][/ROW]
[ROW][C][3500,4000[[/C][C]3750[/C][C]20[/C][C]0.15873[/C][C]0.944444[/C][C]0.000317[/C][/ROW]
[ROW][C][4000,4500[[/C][C]4250[/C][C]5[/C][C]0.039683[/C][C]0.984127[/C][C]7.9e-05[/C][/ROW]
[ROW][C][4500,5000][/C][C]4750[/C][C]2[/C][C]0.015873[/C][C]1[/C][C]3.2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299011&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299011&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
[1000,1500[125010.0079370.0079371.6e-05
[1500,2000[1750000.0079370
[2000,2500[225060.0476190.0555569.5e-05
[2500,3000[2750420.3333330.3888890.000667
[3000,3500[3250500.3968250.7857140.000794
[3500,4000[3750200.158730.9444440.000317
[4000,4500[425050.0396830.9841277.9e-05
[4500,5000]475020.01587313.2e-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')
}