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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 07 Dec 2017 11:38:14 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/07/t15126434195zpkwwlzht7vmui.htm/, Retrieved Wed, 15 May 2024 16:01:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308676, Retrieved Wed, 15 May 2024 16:01:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram & Frequ...] [2017-12-07 10:38:14] [624f75095443dc501dbf5befeca42dec] [Current]
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Dataseries X:
'AL'
'LA'
'WI'
'CA'
'OH'
'AZ'
'CA'
'CA'
'TX'
'MI'
'CA'
'CA'
'IN'
'IN'
'TN'
'GA'
'VA'
'CA'
'CA'
'CA'
'NE'
'KS'
'CA'
'OK'
'OR'
'NH'
'CA'
'FL'
'TX'
'CA'
'MA'
'TN'
'AL'
'GA'
'PA'
'GA'
'GA'
'CA'
'WA'
'AR'
'GA'
'OK'
'FL'
'IA'
'CA'
'TX'
'GA'
'NC'
'NM'
'OK'
'DC'
'FL'
'OH'
'TX'
'ID'
'CA'
'OR'
'CA'
'CO'
'CA'
'KS'
'OR'
'HI'
'KY'
'FL'
'CA'
'AZ'
'KY'
'FL'
'MI'
'FL'
'TX'
'CA'
'CA'
'SC'
'AZ'
'KY'
'AR'
'OR'
'GA'
'VA'
'WV'
'UT'
'TX'
'MO'
'GA'
'FL'
'MD'
'NY'
'NE'
'TX'
'AZ'
'WA'
'FL'
'NE'
'AZ'
'NJ'
'MD'
'OK'
'MD'
'SC'
'IL'
'ID'
'FL'
'CO'
'TX'
'CA'
'NC'
'MI'
'PA'
'OK'
'OH'
'NY'
'LA'
'CT'
'CA'
'CA'
'KS'
'NC'
'LA'
'FL'
'NY'
'CA'
'NY'
'FL'
'TX'
'LA'
'MI'
'CA'
'AZ'
'CA'
'GA'
'VA'
'IN'
'NY'
'IL'
'MS'
'SC'
'IN'
'MA'
'TX'
'AL'
'CA'
'MD'
'CA'
'TX'
'NJ'
'AZ'
'OK'
'AZ'
'OK'
'TX'
'AZ'
'CA'
'CA'
'NM'
'TX'
'MD'
'NY'
'AL'
'CA'
'NV'
'TX'
'MO'
'MD'
'CA'
'FL'
'MA'
'OK'
'OK'
'CA'
'IN'
'AL'
'OK'
'FL'
'IN'
'FL'
'GA'
'WV'
'OH'
'CA'
'OK'
'MS'
'KY'
'NJ'
'TX'
'NC'
'MO'
'IL'
'FL'
'MI'
'FL'
'NC'
'UT'
'TX'
'SC'
'CO'
'NY'
'TN'
'MO'
'CA'
'OK'
'CO'
'LA'
'WA'
'NC'
'FL'
'LA'
'NM'
'NJ'
'NC'
'MD'
'CA'
'OH'
'FL'
'CA'
'VA'
'IL'
'KY'
'UT'
'GA'
'HI'
'FL'
'SC'
'FL'
'OH'
'SC'
'PA'
'PA'
'CO'
'LA'
'TX'
'AZ'
'TN'
'NV'
'MS'
'FL'
'MT'
'NM'
'KS'
'CA'
'AK'
'AZ'
'OH'
'NY'
'CA'
'AR'
'TX'
'FL'
'TX'
'CA'
'CA'
'WI'
'IL'
'FL'
'OK'
'CA'
'AZ'
'CA'
'AZ'
'TX'
'IL'
'AZ'
'MN'
'FL'
'IL'
'CA'
'NY'
'CO'
'AZ'
'TX'
'AZ'
'FL'
'OK'
'AZ'
'GA'
'ME'
'DE'
'IN'
'NJ'
'UT'
'SC'
'TX'
'MI'
'TX'
'AK'
'FL'
'MO'
'PA'
'NC'
'OR'
'MD'
'MT'
'WA'
'NY'
'CO'
'CA'
'CA'
'IN'
'MN'
'NE'
'VA'
'MO'
'OR'
'IL'
'OK'
'TN'
'FL'
'CA'
'GA'
'TN'
'CA'
'CA'
'MI'
'AZ'
'CA'
'KY'
'ID'
'KY'
'NC'
'MO'
'MO'
'HI'
'PA'
'DE'
'NY'
'CO'
'GA'
'TX'
'WA'
'CA'
'WA'
'TX'
'CO'
'VA'
'LA'
'OK'
'MA'
'CA'
'IA'
'GA'
'AZ'
'WY'
'TX'
'NJ'
'LA'
'CO'
'CA'
'CA'
'CA'
'MA'
'CA'
'TX'
'CA'
'SC'
'TX'
'CA'
'NJ'
'MN'
'OK'
'KS'
'MN'
'TX'
'OK'
'PA'
'TX'
'NY'
'TX'
'KS'
'LA'
'MD'
'WA'
'OR'
'CA'
'TX'
'TX'
'VA'
'LA'
'OH'
'CA'
'CA'
'FL'
'CA'
'MS'
'OK'
'CA'
'TX'
'IL'
'TX'
'WA'
'AZ'
'CA'
'NV'
'AZ'
'MN'
'TX'
'TX'
'CA'
'MI'
'CA'
'AL'
'IL'
'AZ'
'NJ'
'HI'
'CA'
'MN'
'AL'
'CO'
'AZ'
'WA'
'MS'
'WI'
'NJ'
'OK'
'MI'
'OH'
'MD'
'OK'
'FL'
'MO'
'OH'
'MO'
'UT'
'CA'
'TX'
'NE'
'NM'
'CA'
'CO'
'IL'
'WI'
'TX'
'MS'
'OK'
'ID'
'WI'
'NE'
'TX'
'CA'
'NY'
'VA'
'SC'
'TX'
'TX'
'AL'
'VA'
'WA'
'NC'
'CA'




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308676&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308676&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
CA700.1556
TX420.0933
FL290.0644
AZ230.0511
OK220.0489
GA150.0333
NY130.0289
CO120.0267
IL110.0244
LA110.0244
MD100.0222
MO100.0222
NC100.0222
OH100.0222
WA100.0222
MI90.02
NJ90.02
SC90.02
VA90.02
AL80.0178
IN80.0178
KY70.0156
OR70.0156
PA70.0156
KS60.0133
MN60.0133
MS60.0133
NE60.0133
TN60.0133
MA50.0111
NM50.0111
UT50.0111
WI50.0111
HI40.0089
ID40.0089
AR30.0067
NV30.0067
AK20.0044
DE20.0044
IA20.0044
MT20.0044
WV20.0044
CT10.0022
DC10.0022
ME10.0022
NH10.0022
WY10.0022

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
CA & 70 & 0.1556 \tabularnewline
TX & 42 & 0.0933 \tabularnewline
FL & 29 & 0.0644 \tabularnewline
AZ & 23 & 0.0511 \tabularnewline
OK & 22 & 0.0489 \tabularnewline
GA & 15 & 0.0333 \tabularnewline
NY & 13 & 0.0289 \tabularnewline
CO & 12 & 0.0267 \tabularnewline
IL & 11 & 0.0244 \tabularnewline
LA & 11 & 0.0244 \tabularnewline
MD & 10 & 0.0222 \tabularnewline
MO & 10 & 0.0222 \tabularnewline
NC & 10 & 0.0222 \tabularnewline
OH & 10 & 0.0222 \tabularnewline
WA & 10 & 0.0222 \tabularnewline
MI & 9 & 0.02 \tabularnewline
NJ & 9 & 0.02 \tabularnewline
SC & 9 & 0.02 \tabularnewline
VA & 9 & 0.02 \tabularnewline
AL & 8 & 0.0178 \tabularnewline
IN & 8 & 0.0178 \tabularnewline
KY & 7 & 0.0156 \tabularnewline
OR & 7 & 0.0156 \tabularnewline
PA & 7 & 0.0156 \tabularnewline
KS & 6 & 0.0133 \tabularnewline
MN & 6 & 0.0133 \tabularnewline
MS & 6 & 0.0133 \tabularnewline
NE & 6 & 0.0133 \tabularnewline
TN & 6 & 0.0133 \tabularnewline
MA & 5 & 0.0111 \tabularnewline
NM & 5 & 0.0111 \tabularnewline
UT & 5 & 0.0111 \tabularnewline
WI & 5 & 0.0111 \tabularnewline
HI & 4 & 0.0089 \tabularnewline
ID & 4 & 0.0089 \tabularnewline
AR & 3 & 0.0067 \tabularnewline
NV & 3 & 0.0067 \tabularnewline
AK & 2 & 0.0044 \tabularnewline
DE & 2 & 0.0044 \tabularnewline
IA & 2 & 0.0044 \tabularnewline
MT & 2 & 0.0044 \tabularnewline
WV & 2 & 0.0044 \tabularnewline
CT & 1 & 0.0022 \tabularnewline
DC & 1 & 0.0022 \tabularnewline
ME & 1 & 0.0022 \tabularnewline
NH & 1 & 0.0022 \tabularnewline
WY & 1 & 0.0022 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308676&T=1

[TABLE]
[ROW][C]Frequency Table (Categorical Data)[/C][/ROW]
[ROW][C]Category[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][/ROW]
[ROW][C]CA[/C][C]70[/C][C]0.1556[/C][/ROW]
[ROW][C]TX[/C][C]42[/C][C]0.0933[/C][/ROW]
[ROW][C]FL[/C][C]29[/C][C]0.0644[/C][/ROW]
[ROW][C]AZ[/C][C]23[/C][C]0.0511[/C][/ROW]
[ROW][C]OK[/C][C]22[/C][C]0.0489[/C][/ROW]
[ROW][C]GA[/C][C]15[/C][C]0.0333[/C][/ROW]
[ROW][C]NY[/C][C]13[/C][C]0.0289[/C][/ROW]
[ROW][C]CO[/C][C]12[/C][C]0.0267[/C][/ROW]
[ROW][C]IL[/C][C]11[/C][C]0.0244[/C][/ROW]
[ROW][C]LA[/C][C]11[/C][C]0.0244[/C][/ROW]
[ROW][C]MD[/C][C]10[/C][C]0.0222[/C][/ROW]
[ROW][C]MO[/C][C]10[/C][C]0.0222[/C][/ROW]
[ROW][C]NC[/C][C]10[/C][C]0.0222[/C][/ROW]
[ROW][C]OH[/C][C]10[/C][C]0.0222[/C][/ROW]
[ROW][C]WA[/C][C]10[/C][C]0.0222[/C][/ROW]
[ROW][C]MI[/C][C]9[/C][C]0.02[/C][/ROW]
[ROW][C]NJ[/C][C]9[/C][C]0.02[/C][/ROW]
[ROW][C]SC[/C][C]9[/C][C]0.02[/C][/ROW]
[ROW][C]VA[/C][C]9[/C][C]0.02[/C][/ROW]
[ROW][C]AL[/C][C]8[/C][C]0.0178[/C][/ROW]
[ROW][C]IN[/C][C]8[/C][C]0.0178[/C][/ROW]
[ROW][C]KY[/C][C]7[/C][C]0.0156[/C][/ROW]
[ROW][C]OR[/C][C]7[/C][C]0.0156[/C][/ROW]
[ROW][C]PA[/C][C]7[/C][C]0.0156[/C][/ROW]
[ROW][C]KS[/C][C]6[/C][C]0.0133[/C][/ROW]
[ROW][C]MN[/C][C]6[/C][C]0.0133[/C][/ROW]
[ROW][C]MS[/C][C]6[/C][C]0.0133[/C][/ROW]
[ROW][C]NE[/C][C]6[/C][C]0.0133[/C][/ROW]
[ROW][C]TN[/C][C]6[/C][C]0.0133[/C][/ROW]
[ROW][C]MA[/C][C]5[/C][C]0.0111[/C][/ROW]
[ROW][C]NM[/C][C]5[/C][C]0.0111[/C][/ROW]
[ROW][C]UT[/C][C]5[/C][C]0.0111[/C][/ROW]
[ROW][C]WI[/C][C]5[/C][C]0.0111[/C][/ROW]
[ROW][C]HI[/C][C]4[/C][C]0.0089[/C][/ROW]
[ROW][C]ID[/C][C]4[/C][C]0.0089[/C][/ROW]
[ROW][C]AR[/C][C]3[/C][C]0.0067[/C][/ROW]
[ROW][C]NV[/C][C]3[/C][C]0.0067[/C][/ROW]
[ROW][C]AK[/C][C]2[/C][C]0.0044[/C][/ROW]
[ROW][C]DE[/C][C]2[/C][C]0.0044[/C][/ROW]
[ROW][C]IA[/C][C]2[/C][C]0.0044[/C][/ROW]
[ROW][C]MT[/C][C]2[/C][C]0.0044[/C][/ROW]
[ROW][C]WV[/C][C]2[/C][C]0.0044[/C][/ROW]
[ROW][C]CT[/C][C]1[/C][C]0.0022[/C][/ROW]
[ROW][C]DC[/C][C]1[/C][C]0.0022[/C][/ROW]
[ROW][C]ME[/C][C]1[/C][C]0.0022[/C][/ROW]
[ROW][C]NH[/C][C]1[/C][C]0.0022[/C][/ROW]
[ROW][C]WY[/C][C]1[/C][C]0.0022[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308676&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 (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
CA700.1556
TX420.0933
FL290.0644
AZ230.0511
OK220.0489
GA150.0333
NY130.0289
CO120.0267
IL110.0244
LA110.0244
MD100.0222
MO100.0222
NC100.0222
OH100.0222
WA100.0222
MI90.02
NJ90.02
SC90.02
VA90.02
AL80.0178
IN80.0178
KY70.0156
OR70.0156
PA70.0156
KS60.0133
MN60.0133
MS60.0133
NE60.0133
TN60.0133
MA50.0111
NM50.0111
UT50.0111
WI50.0111
HI40.0089
ID40.0089
AR30.0067
NV30.0067
AK20.0044
DE20.0044
IA20.0044
MT20.0044
WV20.0044
CT10.0022
DC10.0022
ME10.0022
NH10.0022
WY10.0022



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 {
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,'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')
}