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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 computationMon, 23 Nov 2015 15:35:22 +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/2015/Nov/23/t1448293110jetvr43qumki09m.htm/, Retrieved Tue, 14 May 2024 05:03:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283934, Retrieved Tue, 14 May 2024 05:03:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Werkloosheid vrouwen] [2015-11-23 15:35:22] [6fcd835d84c21d5fa75424c2b64e5f0f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
221
219
214
210
207
206
217
231
234
233
228
226
227
225
219
215
210
206
215
228
229
222
215
212
211
208
205
201
198
198
210
224
226
222
216
215
215
214
211
207
203
200
209
223
225
216
206
203
203
201
197
192
187
184
194
203
197
191
182
175
163
155
151
156
154
153
167
177
171
169
160
151
139
130
126
130
127
122
129
135
142
156
157
165
170
169
162
148
143
146
175
181
178
166
161
164
173
174
167
156
148
150
174
181
183
178
176
184
193
192
182
163
157
167
205
219
214
198
183
184
192
196
194
185
181
184
206
210
208
197
189
190
191
190
187
184
183
184
203
208
205
195
189
188
190
190
190
193
185
173
176
170
163
170
171
173
171
162
152
142
136
146
179
191
181
170
161
168
180
182
176
164
154
160
189
196
186
171
169
181
198
202
196
183
173
175
198
203
197
191
182
172
158
147
143
146
147
152
177
184
174
162
157
155
159
158
156
157
156
158
173
179
172
169
168
172
180
182
182
181
178
178
196
199
192
187
184
184
188
183
176
168
163
166
189
195
192
189
187
187
190
187
179
168
160
161
177
182
176

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283934&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]0 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=283934&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283934&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[120,130[12540.0160640.0160640.001606
[130,140[13550.020080.0361450.002008
[140,150[145110.0441770.0803210.004418
[150,160[155230.0923690.1726910.009237
[160,170[165290.1164660.2891570.011647
[170,180[175370.1485940.4377510.014859
[180,190[185450.1807230.6184740.018072
[190,200[195350.1405620.7590360.014056
[200,210[205230.0923690.8514060.009237
[210,220[215210.0843370.9357430.008434
[220,230[225130.0522090.9879520.005221
[230,240]23530.01204810.001205

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[120,130[ & 125 & 4 & 0.016064 & 0.016064 & 0.001606 \tabularnewline
[130,140[ & 135 & 5 & 0.02008 & 0.036145 & 0.002008 \tabularnewline
[140,150[ & 145 & 11 & 0.044177 & 0.080321 & 0.004418 \tabularnewline
[150,160[ & 155 & 23 & 0.092369 & 0.172691 & 0.009237 \tabularnewline
[160,170[ & 165 & 29 & 0.116466 & 0.289157 & 0.011647 \tabularnewline
[170,180[ & 175 & 37 & 0.148594 & 0.437751 & 0.014859 \tabularnewline
[180,190[ & 185 & 45 & 0.180723 & 0.618474 & 0.018072 \tabularnewline
[190,200[ & 195 & 35 & 0.140562 & 0.759036 & 0.014056 \tabularnewline
[200,210[ & 205 & 23 & 0.092369 & 0.851406 & 0.009237 \tabularnewline
[210,220[ & 215 & 21 & 0.084337 & 0.935743 & 0.008434 \tabularnewline
[220,230[ & 225 & 13 & 0.052209 & 0.987952 & 0.005221 \tabularnewline
[230,240] & 235 & 3 & 0.012048 & 1 & 0.001205 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283934&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][120,130[[/C][C]125[/C][C]4[/C][C]0.016064[/C][C]0.016064[/C][C]0.001606[/C][/ROW]
[ROW][C][130,140[[/C][C]135[/C][C]5[/C][C]0.02008[/C][C]0.036145[/C][C]0.002008[/C][/ROW]
[ROW][C][140,150[[/C][C]145[/C][C]11[/C][C]0.044177[/C][C]0.080321[/C][C]0.004418[/C][/ROW]
[ROW][C][150,160[[/C][C]155[/C][C]23[/C][C]0.092369[/C][C]0.172691[/C][C]0.009237[/C][/ROW]
[ROW][C][160,170[[/C][C]165[/C][C]29[/C][C]0.116466[/C][C]0.289157[/C][C]0.011647[/C][/ROW]
[ROW][C][170,180[[/C][C]175[/C][C]37[/C][C]0.148594[/C][C]0.437751[/C][C]0.014859[/C][/ROW]
[ROW][C][180,190[[/C][C]185[/C][C]45[/C][C]0.180723[/C][C]0.618474[/C][C]0.018072[/C][/ROW]
[ROW][C][190,200[[/C][C]195[/C][C]35[/C][C]0.140562[/C][C]0.759036[/C][C]0.014056[/C][/ROW]
[ROW][C][200,210[[/C][C]205[/C][C]23[/C][C]0.092369[/C][C]0.851406[/C][C]0.009237[/C][/ROW]
[ROW][C][210,220[[/C][C]215[/C][C]21[/C][C]0.084337[/C][C]0.935743[/C][C]0.008434[/C][/ROW]
[ROW][C][220,230[[/C][C]225[/C][C]13[/C][C]0.052209[/C][C]0.987952[/C][C]0.005221[/C][/ROW]
[ROW][C][230,240][/C][C]235[/C][C]3[/C][C]0.012048[/C][C]1[/C][C]0.001205[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283934&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283934&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
[120,130[12540.0160640.0160640.001606
[130,140[13550.020080.0361450.002008
[140,150[145110.0441770.0803210.004418
[150,160[155230.0923690.1726910.009237
[160,170[165290.1164660.2891570.011647
[170,180[175370.1485940.4377510.014859
[180,190[185450.1807230.6184740.018072
[190,200[195350.1405620.7590360.014056
[200,210[205230.0923690.8514060.009237
[210,220[215210.0843370.9357430.008434
[220,230[225130.0522090.9879520.005221
[230,240]23530.01204810.001205


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 {
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')
}