Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_fitdistrnorm.wasp
Title produced by softwareML Fitting and QQ Plot- Normal Distribution
Date of computationTue, 21 Apr 2020 17:18:48 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Apr/21/t1587484285dxyox4lugqr5gov.htm/, Retrieved Sat, 15 May 2021 23:59:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319139, Retrieved Sat, 15 May 2021 23:59:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact46
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [ML Fitting and QQ Plot- Normal Distribution] [] [2020-04-21 15:18:48] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
$62,897,210.20
$63,174,413.18
$67,201,224.66
$68,973,979.92
$52,190,577.71
$61,079,762.12
$60,602,326.05
$80,045,781.80
$63,348,002.01
$70,379,096.07
$57,579,682.80
$59,434,016.55
$58,259,927.53
$60,806,054.54
$66,296,678.07
$66,601,187.53
$67,694,923.94
$65,798,390.32
$62,111,206.30
$66,977,264.43
$59,111,920.01
$53,488,848.05
$53,985,223.72
$62,766,088.16
$58,102,681.96
$68,715,070.51
$66,952,517.50
$66,529,466.40
$71,513,797.44
$67,518,599.51
$70,881,629.67
$74,068,747.43
$73,348,701.17
$74,418,791.76
$83,778,135.12
$82,054,671.92
$83,909,739.64
$79,179,168.58
$74,697,490.36
$76,996,320.79
$77,924,713.88
$77,257,423.85
$91,579,952.10
$95,295,918.81
$93,023,164.41
$92,592,734.65
$95,612,377.01
$97,493,588.08
$95,460,766.25
$97,589,841.71
$116,455,733.38
$123,758,776.11




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319139&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319139&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319139&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 time0 seconds
R ServerBig Analytics Cloud Computing Center



Parameters (Session):
par1 = 8 ; par2 = 0 ;
Parameters (R input):
par1 = 8 ; par2 = 0 ;
R code (references can be found in the software module):
library(MASS)
library(car)
par1 <- as.numeric(par1)
if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
r <- fitdistr(x,'normal')
print(r)
bitmap(file='test1.png')
myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F)
curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)
dev.off()
bitmap(file='test3.png')
qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$estimate[1])
a<-table.element(a,r$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'standard deviation',header=TRUE)
a<-table.element(a,r$estimate[2])
a<-table.element(a,r$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')