Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 09 Aug 2016 08:49:30 +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/Aug/09/t1470729006dfj64fk0prir4h8.htm/, Retrieved Fri, 20 Sep 2024 23:55:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296127, Retrieved Fri, 20 Sep 2024 23:55:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2016-08-09 07:18:36] [ba9845715efdcdf5bf90594b26d5ea9c]
-   PD  [Univariate Data Series] [] [2016-08-09 07:23:22] [ba9845715efdcdf5bf90594b26d5ea9c]
- RMPD      [Histogram] [] [2016-08-09 07:49:30] [eed3b94f44ab74d862a61d666a631b56] [Current]
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Dataseries X:
7263.63
7135.88
7008.00
6752.38
9339.00
9211.13
7263.63
5970.38
6098.13
6098.13
6226.00
6495.50
5714.75
4932.75
4292.38
4292.38
6752.38
7008.00
5060.50
2857.38
4022.88
4022.88
4932.75
5457.88
5330.00
4022.88
4677.13
4420.25
6623.38
6098.13
4022.88
2472.75
3895.00
4292.38
4677.13
5188.38
4150.63
3254.75
3639.50
3767.25
7135.88
7135.88
5188.38
4932.75
5714.75
5330.00
6367.75
7661.00
7917.88
6098.13
5585.63
5060.50
8570.88
8827.75
8173.50
8827.75
8698.63
7661.00
8827.75
10121.00
10646.13
9083.38
8045.63
8827.75
12196.25
13234.00
12978.38
13489.50
13361.75
12068.50
14271.63
14796.75
15564.88
13234.00
12324.13
13361.75
15834.38
18037.50
17512.38
17512.38
17769.25
16872.00
19204.25
19204.25
18806.88
16602.50
16999.88
17256.75
18947.38
21150.50
19587.63
20369.75
19715.50
19332.00
22317.25
21663.00
20753.13
19459.88
20753.13
21407.38
22188.13
23225.75
22188.13
22828.50
22047.63
21919.88
25160.63
25430.13
24392.50
22572.88
24123.00
24776.00
25558.00
26723.50
25558.00
26467.88
26070.50
24648.13
27633.25
27633.25




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296127&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296127&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296127&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[2000,3000[250020.0166670.0166671.7e-05
[3000,4000[350040.0333330.053.3e-05
[4000,5000[4500140.1166670.1666670.000117
[5000,6000[5500110.0916670.2583339.2e-05
[6000,7000[6500100.0833330.3416678.3e-05
[7000,8000[7500100.0833330.4258.3e-05
[8000,9000[850080.0666670.4916676.7e-05
[9000,10000[950030.0250.5166672.5e-05
[10000,11000[1050020.0166670.5333331.7e-05
[11000,12000[11500000.5333330
[12000,13000[1250040.0333330.5666673.3e-05
[13000,14000[1350050.0416670.6083334.2e-05
[14000,15000[1450020.0166670.6251.7e-05
[15000,16000[1550020.0166670.6416671.7e-05
[16000,17000[1650030.0250.6666672.5e-05
[17000,18000[1750040.0333330.73.3e-05
[18000,19000[1850030.0250.7252.5e-05
[19000,20000[1950060.050.7755e-05
[20000,21000[2050030.0250.82.5e-05
[21000,22000[2150040.0333330.8333333.3e-05
[22000,23000[2250060.050.8833335e-05
[23000,24000[2350010.0083330.8916678e-06
[24000,25000[2450040.0333330.9253.3e-05
[25000,26000[2550040.0333330.9583333.3e-05
[26000,27000[2650030.0250.9833332.5e-05
[27000,28000]2750020.01666711.7e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2000,3000[ & 2500 & 2 & 0.016667 & 0.016667 & 1.7e-05 \tabularnewline
[3000,4000[ & 3500 & 4 & 0.033333 & 0.05 & 3.3e-05 \tabularnewline
[4000,5000[ & 4500 & 14 & 0.116667 & 0.166667 & 0.000117 \tabularnewline
[5000,6000[ & 5500 & 11 & 0.091667 & 0.258333 & 9.2e-05 \tabularnewline
[6000,7000[ & 6500 & 10 & 0.083333 & 0.341667 & 8.3e-05 \tabularnewline
[7000,8000[ & 7500 & 10 & 0.083333 & 0.425 & 8.3e-05 \tabularnewline
[8000,9000[ & 8500 & 8 & 0.066667 & 0.491667 & 6.7e-05 \tabularnewline
[9000,10000[ & 9500 & 3 & 0.025 & 0.516667 & 2.5e-05 \tabularnewline
[10000,11000[ & 10500 & 2 & 0.016667 & 0.533333 & 1.7e-05 \tabularnewline
[11000,12000[ & 11500 & 0 & 0 & 0.533333 & 0 \tabularnewline
[12000,13000[ & 12500 & 4 & 0.033333 & 0.566667 & 3.3e-05 \tabularnewline
[13000,14000[ & 13500 & 5 & 0.041667 & 0.608333 & 4.2e-05 \tabularnewline
[14000,15000[ & 14500 & 2 & 0.016667 & 0.625 & 1.7e-05 \tabularnewline
[15000,16000[ & 15500 & 2 & 0.016667 & 0.641667 & 1.7e-05 \tabularnewline
[16000,17000[ & 16500 & 3 & 0.025 & 0.666667 & 2.5e-05 \tabularnewline
[17000,18000[ & 17500 & 4 & 0.033333 & 0.7 & 3.3e-05 \tabularnewline
[18000,19000[ & 18500 & 3 & 0.025 & 0.725 & 2.5e-05 \tabularnewline
[19000,20000[ & 19500 & 6 & 0.05 & 0.775 & 5e-05 \tabularnewline
[20000,21000[ & 20500 & 3 & 0.025 & 0.8 & 2.5e-05 \tabularnewline
[21000,22000[ & 21500 & 4 & 0.033333 & 0.833333 & 3.3e-05 \tabularnewline
[22000,23000[ & 22500 & 6 & 0.05 & 0.883333 & 5e-05 \tabularnewline
[23000,24000[ & 23500 & 1 & 0.008333 & 0.891667 & 8e-06 \tabularnewline
[24000,25000[ & 24500 & 4 & 0.033333 & 0.925 & 3.3e-05 \tabularnewline
[25000,26000[ & 25500 & 4 & 0.033333 & 0.958333 & 3.3e-05 \tabularnewline
[26000,27000[ & 26500 & 3 & 0.025 & 0.983333 & 2.5e-05 \tabularnewline
[27000,28000] & 27500 & 2 & 0.016667 & 1 & 1.7e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296127&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][2000,3000[[/C][C]2500[/C][C]2[/C][C]0.016667[/C][C]0.016667[/C][C]1.7e-05[/C][/ROW]
[ROW][C][3000,4000[[/C][C]3500[/C][C]4[/C][C]0.033333[/C][C]0.05[/C][C]3.3e-05[/C][/ROW]
[ROW][C][4000,5000[[/C][C]4500[/C][C]14[/C][C]0.116667[/C][C]0.166667[/C][C]0.000117[/C][/ROW]
[ROW][C][5000,6000[[/C][C]5500[/C][C]11[/C][C]0.091667[/C][C]0.258333[/C][C]9.2e-05[/C][/ROW]
[ROW][C][6000,7000[[/C][C]6500[/C][C]10[/C][C]0.083333[/C][C]0.341667[/C][C]8.3e-05[/C][/ROW]
[ROW][C][7000,8000[[/C][C]7500[/C][C]10[/C][C]0.083333[/C][C]0.425[/C][C]8.3e-05[/C][/ROW]
[ROW][C][8000,9000[[/C][C]8500[/C][C]8[/C][C]0.066667[/C][C]0.491667[/C][C]6.7e-05[/C][/ROW]
[ROW][C][9000,10000[[/C][C]9500[/C][C]3[/C][C]0.025[/C][C]0.516667[/C][C]2.5e-05[/C][/ROW]
[ROW][C][10000,11000[[/C][C]10500[/C][C]2[/C][C]0.016667[/C][C]0.533333[/C][C]1.7e-05[/C][/ROW]
[ROW][C][11000,12000[[/C][C]11500[/C][C]0[/C][C]0[/C][C]0.533333[/C][C]0[/C][/ROW]
[ROW][C][12000,13000[[/C][C]12500[/C][C]4[/C][C]0.033333[/C][C]0.566667[/C][C]3.3e-05[/C][/ROW]
[ROW][C][13000,14000[[/C][C]13500[/C][C]5[/C][C]0.041667[/C][C]0.608333[/C][C]4.2e-05[/C][/ROW]
[ROW][C][14000,15000[[/C][C]14500[/C][C]2[/C][C]0.016667[/C][C]0.625[/C][C]1.7e-05[/C][/ROW]
[ROW][C][15000,16000[[/C][C]15500[/C][C]2[/C][C]0.016667[/C][C]0.641667[/C][C]1.7e-05[/C][/ROW]
[ROW][C][16000,17000[[/C][C]16500[/C][C]3[/C][C]0.025[/C][C]0.666667[/C][C]2.5e-05[/C][/ROW]
[ROW][C][17000,18000[[/C][C]17500[/C][C]4[/C][C]0.033333[/C][C]0.7[/C][C]3.3e-05[/C][/ROW]
[ROW][C][18000,19000[[/C][C]18500[/C][C]3[/C][C]0.025[/C][C]0.725[/C][C]2.5e-05[/C][/ROW]
[ROW][C][19000,20000[[/C][C]19500[/C][C]6[/C][C]0.05[/C][C]0.775[/C][C]5e-05[/C][/ROW]
[ROW][C][20000,21000[[/C][C]20500[/C][C]3[/C][C]0.025[/C][C]0.8[/C][C]2.5e-05[/C][/ROW]
[ROW][C][21000,22000[[/C][C]21500[/C][C]4[/C][C]0.033333[/C][C]0.833333[/C][C]3.3e-05[/C][/ROW]
[ROW][C][22000,23000[[/C][C]22500[/C][C]6[/C][C]0.05[/C][C]0.883333[/C][C]5e-05[/C][/ROW]
[ROW][C][23000,24000[[/C][C]23500[/C][C]1[/C][C]0.008333[/C][C]0.891667[/C][C]8e-06[/C][/ROW]
[ROW][C][24000,25000[[/C][C]24500[/C][C]4[/C][C]0.033333[/C][C]0.925[/C][C]3.3e-05[/C][/ROW]
[ROW][C][25000,26000[[/C][C]25500[/C][C]4[/C][C]0.033333[/C][C]0.958333[/C][C]3.3e-05[/C][/ROW]
[ROW][C][26000,27000[[/C][C]26500[/C][C]3[/C][C]0.025[/C][C]0.983333[/C][C]2.5e-05[/C][/ROW]
[ROW][C][27000,28000][/C][C]27500[/C][C]2[/C][C]0.016667[/C][C]1[/C][C]1.7e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296127&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296127&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[2000,3000[250020.0166670.0166671.7e-05
[3000,4000[350040.0333330.053.3e-05
[4000,5000[4500140.1166670.1666670.000117
[5000,6000[5500110.0916670.2583339.2e-05
[6000,7000[6500100.0833330.3416678.3e-05
[7000,8000[7500100.0833330.4258.3e-05
[8000,9000[850080.0666670.4916676.7e-05
[9000,10000[950030.0250.5166672.5e-05
[10000,11000[1050020.0166670.5333331.7e-05
[11000,12000[11500000.5333330
[12000,13000[1250040.0333330.5666673.3e-05
[13000,14000[1350050.0416670.6083334.2e-05
[14000,15000[1450020.0166670.6251.7e-05
[15000,16000[1550020.0166670.6416671.7e-05
[16000,17000[1650030.0250.6666672.5e-05
[17000,18000[1750040.0333330.73.3e-05
[18000,19000[1850030.0250.7252.5e-05
[19000,20000[1950060.050.7755e-05
[20000,21000[2050030.0250.82.5e-05
[21000,22000[2150040.0333330.8333333.3e-05
[22000,23000[2250060.050.8833335e-05
[23000,24000[2350010.0083330.8916678e-06
[24000,25000[2450040.0333330.9253.3e-05
[25000,26000[2550040.0333330.9583333.3e-05
[26000,27000[2650030.0250.9833332.5e-05
[27000,28000]2750020.01666711.7e-05



Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '4'
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,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')
}