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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, 21 Oct 2008 01:20:00 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/21/t1224573650f6hdunsz9msjwf7.htm/, Retrieved Sun, 19 May 2024 18:46:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18350, Retrieved Sun, 19 May 2024 18:46:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsaantal niet werkende werkzoekende vrouwen
Estimated Impact143

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] [Aantal niet werke...] [2008-10-13 17:14:43] [b635de6fc42b001d22cbe6e730fec936]
- RMP   [Central Tendency] [Aantal niet werke...] [2008-10-20 17:40:10] [b635de6fc42b001d22cbe6e730fec936]
- RMP       [Histogram] [aantal niet werke...] [2008-10-21 07:20:00] [f4b2017b314c03698059f43b95818e67] [Current]
- RMPD        [Back to Back Histogram] [Histogram kolom 2...] [2008-10-21 07:33:55] [b635de6fc42b001d22cbe6e730fec936]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
308.347
298.427
289.231
291.975
294.912
293.488
290.555
284.736
281.818
287.854
316.263
325.412
326.011
328.282
317.480
317.539
313.737
312.276
309.391
302.950
300.316
304.035
333.476
337.698
335.932
323.931
313.927
314.485
313.218
309.664
302.963
298.989
298.423
301.631
329.765
335.083
327.616
309.119
295.916
291.413
291.542
284.678
276.475
272.566
264.981
263.290
296.806
303.598
286.994
276.427
266.424
267.153
268.381
262.522
255.542
253.158
243.803
250.741
280.445
285.257

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'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18350&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18350&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'Gwilym Jenkins' @ 72.249.127.135






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[240,250[24510.0166670.0166670.001667
[250,260[25530.050.0666670.005
[260,270[26560.10.1666670.01
[270,280[27530.050.2166670.005
[280,290[28580.1333330.350.013333
[290,300[295110.1833330.5333330.018333
[300,310[305100.1666670.70.016667
[310,320[31580.1333330.8333330.013333
[320,330[32560.10.9333330.01
[330,340]33540.06666710.006667

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[240,250[ & 245 & 1 & 0.016667 & 0.016667 & 0.001667 \tabularnewline
[250,260[ & 255 & 3 & 0.05 & 0.066667 & 0.005 \tabularnewline
[260,270[ & 265 & 6 & 0.1 & 0.166667 & 0.01 \tabularnewline
[270,280[ & 275 & 3 & 0.05 & 0.216667 & 0.005 \tabularnewline
[280,290[ & 285 & 8 & 0.133333 & 0.35 & 0.013333 \tabularnewline
[290,300[ & 295 & 11 & 0.183333 & 0.533333 & 0.018333 \tabularnewline
[300,310[ & 305 & 10 & 0.166667 & 0.7 & 0.016667 \tabularnewline
[310,320[ & 315 & 8 & 0.133333 & 0.833333 & 0.013333 \tabularnewline
[320,330[ & 325 & 6 & 0.1 & 0.933333 & 0.01 \tabularnewline
[330,340] & 335 & 4 & 0.066667 & 1 & 0.006667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18350&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][240,250[[/C][C]245[/C][C]1[/C][C]0.016667[/C][C]0.016667[/C][C]0.001667[/C][/ROW]
[ROW][C][250,260[[/C][C]255[/C][C]3[/C][C]0.05[/C][C]0.066667[/C][C]0.005[/C][/ROW]
[ROW][C][260,270[[/C][C]265[/C][C]6[/C][C]0.1[/C][C]0.166667[/C][C]0.01[/C][/ROW]
[ROW][C][270,280[[/C][C]275[/C][C]3[/C][C]0.05[/C][C]0.216667[/C][C]0.005[/C][/ROW]
[ROW][C][280,290[[/C][C]285[/C][C]8[/C][C]0.133333[/C][C]0.35[/C][C]0.013333[/C][/ROW]
[ROW][C][290,300[[/C][C]295[/C][C]11[/C][C]0.183333[/C][C]0.533333[/C][C]0.018333[/C][/ROW]
[ROW][C][300,310[[/C][C]305[/C][C]10[/C][C]0.166667[/C][C]0.7[/C][C]0.016667[/C][/ROW]
[ROW][C][310,320[[/C][C]315[/C][C]8[/C][C]0.133333[/C][C]0.833333[/C][C]0.013333[/C][/ROW]
[ROW][C][320,330[[/C][C]325[/C][C]6[/C][C]0.1[/C][C]0.933333[/C][C]0.01[/C][/ROW]
[ROW][C][330,340][/C][C]335[/C][C]4[/C][C]0.066667[/C][C]1[/C][C]0.006667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18350&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
[240,250[24510.0166670.0166670.001667
[250,260[25530.050.0666670.005
[260,270[26560.10.1666670.01
[270,280[27530.050.2166670.005
[280,290[28580.1333330.350.013333
[290,300[295110.1833330.5333330.018333
[300,310[305100.1666670.70.016667
[310,320[31580.1333330.8333330.013333
[320,330[32560.10.9333330.01
[330,340]33540.06666710.006667


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.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)
}
dev.off()
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')