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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 computationSat, 13 Dec 2014 19:25:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/13/t1418498754yoah6tbf3cko8ow.htm/, Retrieved Thu, 16 May 2024 05:37:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267276, Retrieved Thu, 16 May 2024 05:37:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [histblor] [2014-12-13 19:25:39] [ba449e08135e498de67ac1fe8477f1b8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96
75
70
88
114
69
176
114
121
110
158
116
181
77
141
35
80
152
97
99
84
68
101
107
88
112
171
137
77
66
93
105
131
89
102
161
120
127
77
108
85
168
48
152
75
107
62
121
124
72
40
58
97
88
126
104
148
146
80
97
25
99
118
58
63
139
50
60
152
142
94
66
127
67
90
75
96
128
41
146
69
186
81
85
54
46
106
34
60
95
57
62
36
56
54
64
76
98
88
35
102
61
80
49
78
90
45
55
96
43
52
60
54
51
51
38
41
146
182
192
263
35
439
214
341
58
292
85
200
158
199
297
227
108
86
302
148
178
120
207
157
128
296
323
79
70
146
246
145
196
199
127
91
153
299
228
190
180
212
269
130
179
243
190
299
121
137
305
157
96
183
52
238
40
226
190
214
145
119
222
222
159
165
249
125
122
186
148
274
172
84
168
102
106
2
139
95
130
72
141
113
206
268
175
77
125
255
111
132
211
92
76
171
83
119
266
186
50
117
219
246
279
148
137
130
181
98
226
234
138
85
66
236
106
135
122
218
199
112
278
94
113
84
86
62
222
167
82
207
184
83
183
85
89
225
237
102
221
128
91
198
204
158
138
226
44
196
83
79
52
105
116
83
196
153
157
75
106
58
75
74
185
265
131
139
196
78

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267276&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267276&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267276&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,50[25180.0627180.0627180.001254
[50,100[75990.3449480.4076660.006899
[100,150[125750.2613240.668990.005226
[150,200[175470.1637630.8327530.003275
[200,250[225290.1010450.9337980.002021
[250,300[275140.048780.9825780.000976
[300,350[32540.0139370.9965160.000279
[350,400[375000.9965160
[400,450]42510.00348417e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,50[ & 25 & 18 & 0.062718 & 0.062718 & 0.001254 \tabularnewline
[50,100[ & 75 & 99 & 0.344948 & 0.407666 & 0.006899 \tabularnewline
[100,150[ & 125 & 75 & 0.261324 & 0.66899 & 0.005226 \tabularnewline
[150,200[ & 175 & 47 & 0.163763 & 0.832753 & 0.003275 \tabularnewline
[200,250[ & 225 & 29 & 0.101045 & 0.933798 & 0.002021 \tabularnewline
[250,300[ & 275 & 14 & 0.04878 & 0.982578 & 0.000976 \tabularnewline
[300,350[ & 325 & 4 & 0.013937 & 0.996516 & 0.000279 \tabularnewline
[350,400[ & 375 & 0 & 0 & 0.996516 & 0 \tabularnewline
[400,450] & 425 & 1 & 0.003484 & 1 & 7e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267276&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][0,50[[/C][C]25[/C][C]18[/C][C]0.062718[/C][C]0.062718[/C][C]0.001254[/C][/ROW]
[ROW][C][50,100[[/C][C]75[/C][C]99[/C][C]0.344948[/C][C]0.407666[/C][C]0.006899[/C][/ROW]
[ROW][C][100,150[[/C][C]125[/C][C]75[/C][C]0.261324[/C][C]0.66899[/C][C]0.005226[/C][/ROW]
[ROW][C][150,200[[/C][C]175[/C][C]47[/C][C]0.163763[/C][C]0.832753[/C][C]0.003275[/C][/ROW]
[ROW][C][200,250[[/C][C]225[/C][C]29[/C][C]0.101045[/C][C]0.933798[/C][C]0.002021[/C][/ROW]
[ROW][C][250,300[[/C][C]275[/C][C]14[/C][C]0.04878[/C][C]0.982578[/C][C]0.000976[/C][/ROW]
[ROW][C][300,350[[/C][C]325[/C][C]4[/C][C]0.013937[/C][C]0.996516[/C][C]0.000279[/C][/ROW]
[ROW][C][350,400[[/C][C]375[/C][C]0[/C][C]0[/C][C]0.996516[/C][C]0[/C][/ROW]
[ROW][C][400,450][/C][C]425[/C][C]1[/C][C]0.003484[/C][C]1[/C][C]7e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267276&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267276&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
[0,50[25180.0627180.0627180.001254
[50,100[75990.3449480.4076660.006899
[100,150[125750.2613240.668990.005226
[150,200[175470.1637630.8327530.003275
[200,250[225290.1010450.9337980.002021
[250,300[275140.048780.9825780.000976
[300,350[32540.0139370.9965160.000279
[350,400[375000.9965160
[400,450]42510.00348417e-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 {
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')
}