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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 07 Aug 2012 02:54:24 -0400
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/Aug/07/t1344322488dv49q1ue0dzthvb.htm/, Retrieved Fri, 03 May 2024 06:32:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169047, Retrieved Fri, 03 May 2024 06:32:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan der Smissen Britt
Estimated Impact130

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] [Tijdreeks A-Stap 1] [2012-08-07 06:32:31] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP     [Histogram] [Tijdreeks A-Stap 3] [2012-08-07 06:54:24] [b3616d670e39c9c081ac68ec1f5d1a32] [Current]
- RMP       [Kernel Density Estimation] [Tijdreeks A-Stap 6] [2012-08-08 06:47:30] [e7a19f46406e1c79b79b562d86e5e00b]
- RMPD      [Notched Boxplots] [tijdreeks A-Stap 9] [2012-08-08 07:21:37] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Harrell-Davis Quantiles] [Tijdreeks A-stap 11] [2012-08-08 07:26:07] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Harrell-Davis Quantiles] [Tijdreeks A-stap 12] [2012-08-08 07:36:20] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Central Tendency] [Tijdreeks A-stap 14] [2012-08-08 07:52:26] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Central Tendency] [Tijdreeks A-stap 15] [2012-08-08 07:56:28] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Mean Plot] [tijdreeks A-Stap 17] [2012-08-08 08:13:11] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Standard Deviation Plot] [Tijdreeks A-Stap 23] [2012-08-08 09:00:37] [e7a19f46406e1c79b79b562d86e5e00b]
- RMP       [Standard Deviation-Mean Plot] [Tijdreeks A-Stap 26] [2012-08-08 09:22:39] [e7a19f46406e1c79b79b562d86e5e00b]
- RMPD      [Univariate Data Series] [Tijdreeks B-stap 1] [2012-08-08 11:38:22] [f85cc8f00ef4b762f0a6fdfddc793773]
- RMPD      [Kernel Density Estimation] [Tijdreeks B-Stap 4] [2012-08-08 11:48:09] [e7a19f46406e1c79b79b562d86e5e00b]
-             [Kernel Density Estimation] [Tijdreeks B-stap 4] [2012-08-08 11:56:05] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Notched Boxplots] [Tijdreeks B-Stap 5] [2012-08-08 12:04:47] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Harrell-Davis Quantiles] [Tijdreeks B-Stap 6] [2012-08-08 12:07:17] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Harrell-Davis Quantiles] [Tijdreeks B-Stap 7] [2012-08-08 12:15:37] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Central Tendency] [Tijdreekd B-Stap 9] [2012-08-08 12:19:05] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Variability] [Tijdreeks B-stap 20] [2012-08-08 12:25:46] [e7a19f46406e1c79b79b562d86e5e00b]
- RM          [Standard Deviation-Mean Plot] [Tijdreeks B-stap 21] [2012-08-08 12:34:31] [e7a19f46406e1c79b79b562d86e5e00b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95870
95523
95208
94541
101097
100781
95870
92581
92928
92928
93244
93910
93559
96190
97172
96190
99799
97488
92261
90964
90964
91599
89004
90964
89319
90964
93559
94541
96852
95870
89981
87670
86692
87670
86057
86692
84728
88021
89635
89981
96190
96190
88021
86057
86057
87039
82764
80799
78524
79186
82133
79821
86057
87039
80799
78524
77221
78524
74910
73613
68390
69688
70004
70355
76559
75893
68390
65097
63799
65444
59208
54964
47115
47777
47777
47115
52684
53004
46448
45151
42524
46133
39577
35653
28146
29764
27800
28462
33373
34355
31093
30742
30742
35017
27484
22573
14058
20929
19946
20293
28146
27164
23555
25204
25204
31093
24222
20293
14058
22258
21595
21911
28782
28146
25835
26186
27800
31409
25835
21275

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169047&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169047&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169047&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'Herman Ole Andreas Wold' @ wold.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[10000,20000[1500030.0250.0252e-06
[20000,30000[25000250.2083330.2333332.1e-05
[30000,40000[35000100.0833330.3166678e-06
[40000,50000[4500080.0666670.3833337e-06
[50000,60000[5500040.0333330.4166673e-06
[60000,70000[6500060.050.4666675e-06
[70000,80000[75000120.10.5666671e-05
[80000,90000[85000220.1833330.751.8e-05
[90000,1e+05[95000280.2333330.9833332.3e-05
[1e+05,110000]10500020.01666712e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10000,20000[ & 15000 & 3 & 0.025 & 0.025 & 2e-06 \tabularnewline
[20000,30000[ & 25000 & 25 & 0.208333 & 0.233333 & 2.1e-05 \tabularnewline
[30000,40000[ & 35000 & 10 & 0.083333 & 0.316667 & 8e-06 \tabularnewline
[40000,50000[ & 45000 & 8 & 0.066667 & 0.383333 & 7e-06 \tabularnewline
[50000,60000[ & 55000 & 4 & 0.033333 & 0.416667 & 3e-06 \tabularnewline
[60000,70000[ & 65000 & 6 & 0.05 & 0.466667 & 5e-06 \tabularnewline
[70000,80000[ & 75000 & 12 & 0.1 & 0.566667 & 1e-05 \tabularnewline
[80000,90000[ & 85000 & 22 & 0.183333 & 0.75 & 1.8e-05 \tabularnewline
[90000,1e+05[ & 95000 & 28 & 0.233333 & 0.983333 & 2.3e-05 \tabularnewline
[1e+05,110000] & 105000 & 2 & 0.016667 & 1 & 2e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169047&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][10000,20000[[/C][C]15000[/C][C]3[/C][C]0.025[/C][C]0.025[/C][C]2e-06[/C][/ROW]
[ROW][C][20000,30000[[/C][C]25000[/C][C]25[/C][C]0.208333[/C][C]0.233333[/C][C]2.1e-05[/C][/ROW]
[ROW][C][30000,40000[[/C][C]35000[/C][C]10[/C][C]0.083333[/C][C]0.316667[/C][C]8e-06[/C][/ROW]
[ROW][C][40000,50000[[/C][C]45000[/C][C]8[/C][C]0.066667[/C][C]0.383333[/C][C]7e-06[/C][/ROW]
[ROW][C][50000,60000[[/C][C]55000[/C][C]4[/C][C]0.033333[/C][C]0.416667[/C][C]3e-06[/C][/ROW]
[ROW][C][60000,70000[[/C][C]65000[/C][C]6[/C][C]0.05[/C][C]0.466667[/C][C]5e-06[/C][/ROW]
[ROW][C][70000,80000[[/C][C]75000[/C][C]12[/C][C]0.1[/C][C]0.566667[/C][C]1e-05[/C][/ROW]
[ROW][C][80000,90000[[/C][C]85000[/C][C]22[/C][C]0.183333[/C][C]0.75[/C][C]1.8e-05[/C][/ROW]
[ROW][C][90000,1e+05[[/C][C]95000[/C][C]28[/C][C]0.233333[/C][C]0.983333[/C][C]2.3e-05[/C][/ROW]
[ROW][C][1e+05,110000][/C][C]105000[/C][C]2[/C][C]0.016667[/C][C]1[/C][C]2e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169047&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169047&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
[10000,20000[1500030.0250.0252e-06
[20000,30000[25000250.2083330.2333332.1e-05
[30000,40000[35000100.0833330.3166678e-06
[40000,50000[4500080.0666670.3833337e-06
[50000,60000[5500040.0333330.4166673e-06
[60000,70000[6500060.050.4666675e-06
[70000,80000[75000120.10.5666671e-05
[80000,90000[85000220.1833330.751.8e-05
[90000,1e+05[95000280.2333330.9833332.3e-05
[1e+05,110000]10500020.01666712e-06


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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- ''
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')
}