Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 08 Feb 2010 07:03:15 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Feb/08/t12656379843bctkcoufdej3en.htm/, Retrieved Fri, 20 May 2022 00:34:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72871, Retrieved Fri, 20 May 2022 00:34:20 +0000
QR Codes:

Original text written by user:*Per maand *Vanaf januari 2000 tot en met december 2009 *FEBIAC (, transit niet inbegrepen)
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Datareeks-Inschri...] [2010-02-08 14:03:15] [d6179d2dd52132dbf2d0bdd7a9920856] [Current]
-         [Histogram] [Datareeks-Inschri...] [2010-02-14 20:54:52] [1f3241a8f2363a866734862cbbf73252]
-   P     [Histogram] [Datareeks-Inschri...] [2010-02-14 21:01:02] [1f3241a8f2363a866734862cbbf73252]
- RMP     [Kernel Density Estimation] [Datareeks-Inschri...] [2010-02-14 21:10:25] [1f3241a8f2363a866734862cbbf73252]
- RMP     [Harrell-Davis Quantiles] [Datareeks-Opdrach...] [2010-03-08 17:29:04] [1f3241a8f2363a866734862cbbf73252]
- RMP     [Harrell-Davis Quantiles] [Datareeks-Opdrach...] [2010-03-08 17:35:01] [1f3241a8f2363a866734862cbbf73252]
- RMPD      [Mean Plot] [Opgave 6 oefening...] [2010-04-26 21:57:04] [1f3241a8f2363a866734862cbbf73252]
-    D        [Mean Plot] [Opgave 6 oefening...] [2010-04-28 15:35:23] [1f3241a8f2363a866734862cbbf73252]
- RMPD        [(Partial) Autocorrelation Function] [Opgave 6 BIS oefe...] [2010-05-03 18:06:05] [1f3241a8f2363a866734862cbbf73252]
-   P           [(Partial) Autocorrelation Function] [Opgave 6 BIS oefe...] [2010-05-03 18:08:48] [1f3241a8f2363a866734862cbbf73252]
-   P           [(Partial) Autocorrelation Function] [Opgave 6 BIS oefe...] [2010-05-03 18:11:43] [1f3241a8f2363a866734862cbbf73252]
-   P           [(Partial) Autocorrelation Function] [Opgave 6 BIS oefe...] [2010-05-03 18:13:08] [1f3241a8f2363a866734862cbbf73252]
- RMP     [Harrell-Davis Quantiles] [Datareeks-Opdrach...] [2010-03-08 17:44:01] [1f3241a8f2363a866734862cbbf73252]
- RMPD    [Central Tendency] [Datareeks-Inschri...] [2010-03-11 16:42:49] [1f3241a8f2363a866734862cbbf73252]
- RMPD    [Mean versus Median] [Datareeks-Inschri...] [2010-03-11 16:50:14] [1f3241a8f2363a866734862cbbf73252]
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Dataseries X:
14.538
18.730
22.485
20.036
16.971
19.028
22.759
20.516
26.195
27.786
24.090
25.447
11.509
15.572
22.518
20.520
17.789
20.205
26.835
25.826
31.934
30.019
30.111
31.566
12.738
19.814
24.776
20.424
18.688
20.418
25.778
25.100
25.859
30.651
26.551
31.124
9.367
17.382
20.995
18.205
17.328
18.157
23.691
26.736
27.165
34.506
29.506
31.956
10.698
18.479
19.785
19.684
18.730
17.970
27.044
22.405
26.482
29.096
25.591
29.743
13.807
19.169
22.782
20.366
17.537
18.004
24.319
22.679
32.034
36.438
29.383
28.029
15.548
17.704
25.316
20.764
18.089
21.705
23.843
22.397
26.105
29.462
27.071
31.514
11.514
17.409
24.561
21.382
17.351
22.780
23.970
26.887
34.777
35.022
35.338
36.845
13.971
22.228
28.806
20.506
22.414
25.814
28.352
29.965
30.212
32.609
30.364
37.702
13.253
21.790
27.192
21.725
22.205
24.693
29.133
35.953
37.863
43.129
39.690
41.086




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72871&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]3 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=72871&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72871&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[5,10[7.510.0083330.0083330.001667
[10,15[12.580.0666670.0750.013333
[15,20[17.5240.20.2750.04
[20,25[22.5330.2750.550.055
[25,30[27.5300.250.80.05
[30,35[32.5140.1166670.9166670.023333
[35,40[37.580.0666670.9833330.013333
[40,45]42.520.01666710.003333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[5,10[ & 7.5 & 1 & 0.008333 & 0.008333 & 0.001667 \tabularnewline
[10,15[ & 12.5 & 8 & 0.066667 & 0.075 & 0.013333 \tabularnewline
[15,20[ & 17.5 & 24 & 0.2 & 0.275 & 0.04 \tabularnewline
[20,25[ & 22.5 & 33 & 0.275 & 0.55 & 0.055 \tabularnewline
[25,30[ & 27.5 & 30 & 0.25 & 0.8 & 0.05 \tabularnewline
[30,35[ & 32.5 & 14 & 0.116667 & 0.916667 & 0.023333 \tabularnewline
[35,40[ & 37.5 & 8 & 0.066667 & 0.983333 & 0.013333 \tabularnewline
[40,45] & 42.5 & 2 & 0.016667 & 1 & 0.003333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72871&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][5,10[[/C][C]7.5[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]0.001667[/C][/ROW]
[ROW][C][10,15[[/C][C]12.5[/C][C]8[/C][C]0.066667[/C][C]0.075[/C][C]0.013333[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]24[/C][C]0.2[/C][C]0.275[/C][C]0.04[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]33[/C][C]0.275[/C][C]0.55[/C][C]0.055[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]30[/C][C]0.25[/C][C]0.8[/C][C]0.05[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]14[/C][C]0.116667[/C][C]0.916667[/C][C]0.023333[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]8[/C][C]0.066667[/C][C]0.983333[/C][C]0.013333[/C][/ROW]
[ROW][C][40,45][/C][C]42.5[/C][C]2[/C][C]0.016667[/C][C]1[/C][C]0.003333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72871&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72871&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
[5,10[7.510.0083330.0083330.001667
[10,15[12.580.0666670.0750.013333
[15,20[17.5240.20.2750.04
[20,25[22.5330.2750.550.055
[25,30[27.5300.250.80.05
[30,35[32.5140.1166670.9166670.023333
[35,40[37.580.0666670.9833330.013333
[40,45]42.520.01666710.003333



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')