FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_fitdistrnorm.wasp
Title produced by softwareML Fitting and QQ Plot- Normal Distribution
Date of computationThu, 15 Dec 2016 10:27:42 +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/2016/Dec/15/t1481794115ib056nidz2e61vk.htm/, Retrieved Fri, 01 Nov 2024 03:44:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299788, Retrieved Fri, 01 Nov 2024 03:44:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsN1910
Estimated Impact156

Tree of Dependent Computations

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] [Normal distribution] [2016-12-15 09:27:42] [9a9519454d094169f95f881e5b6f16f7] [Current]
- R       [ML Fitting and QQ Plot- Normal Distribution] [Normal distribution ] [2016-12-15 09:28:47] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMP     [Exponential Smoothing] [Exponential smoot...] [2016-12-15 09:34:17] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Cronbach Alpha] [Cronbach alpha] [2016-12-15 10:08:25] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Cronbach Alpha] [Cronbach alpha IVHB] [2016-12-15 10:11:04] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Cronbach Alpha] [Cronbach alpha be...] [2016-12-15 10:21:45] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Cronbach Alpha] [Cronbach alpha IV...] [2016-12-15 10:28:47] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chisquared simula...] [2016-12-15 10:38:18] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Univariate Data Series] [Plot] [2016-12-21 12:13:06] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Variance Reduction Matrix] [VRM] [2016-12-21 12:16:18] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 12:17:37] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 12:19:52] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2016-12-21 12:20:52] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 12:22:23] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Backward selectio...] [2016-12-21 12:25:13] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Arima backwards p...] [2016-12-21 12:27:09] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Forecasting] [ARIMA forecasting ] [2016-12-21 12:29:45] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Univariate Data Series] [Plot] [2016-12-21 12:32:58] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Variance Reduction Matrix] [VRm] [2016-12-21 12:34:04] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 12:35:07] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 12:36:32] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2016-12-21 12:37:50] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 12:40:01] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-21 13:06:54] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Spectral Analysis] [Spectral analysis] [2016-12-21 13:20:15] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [a] [2017-01-22 21:09:42] [29aab2222b4b721088e78b64014cd237]
- RMPD      [Standard Deviation-Mean Plot] [sd mean plot] [2016-12-21 13:22:01] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [Exponential Smoothing] [Exponential smoot...] [2016-12-21 13:36:48] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Backward Selection] [Arima backwards] [2016-12-21 13:45:55] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD      [ARIMA Forecasting] [ARIMA forecast] [2016-12-21 13:49:45] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chisquared pearson] [2016-12-15 10:42:04] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
-   PD    [ML Fitting and QQ Plot- Normal Distribution] [Normal distributi...] [2016-12-15 10:44:15] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- R PD    [ML Fitting and QQ Plot- Normal Distribution] [Normal distributi...] [2016-12-15 10:50:17] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Notched Boxplots] [Notched bloxpot TVCD] [2016-12-15 10:55:31] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Notched Boxplots] [IVHB notched blox...] [2016-12-15 10:59:30] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Pearson Correlation] [Pearson correlati...] [2016-12-15 11:04:10] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Spearman Rank Correlation] [Rang Correlatie] [2016-12-15 11:09:55] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- RMPD    [Multiple Regression] [Multiple regressi...] [2016-12-15 11:24:47] [061bcad4f8cbfaa4a6cadfe6faec1e5a]
- R P       [Multiple Regression] [] [2016-12-17 09:32:30] [32b17a345b130fdf5cc88718ed94a974]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4738.4
4687.2
5930.8
5532
5429.8
6107.4
5960.8
5541.8
5362.2
5237
4827
4781.6
4983.2
4718.4
5523.8
5286.6
5389
5810.4
5057.4
5604.4
5285
5215.2
4625.4
4270.4
4685.4
4233.8
5278.4
4978.8
5333.4
5451
5224
5790.2
5079.4
4705.8
4139.6
3720.8
4594
4638.8
4969.4
4764.4
5010.8
5267.8
5312.2
5723.2
4579.6
5015.2
4282.4
3834.2
4523.4
3884.2
3897.8
4845.6
4929
4955.4
5198.4
5122.2
4643.2
4789.8
3950.8
3824.4
4511.8
4262.4
4616.6
5139.6
4972.8
5222
5242
4979.8
4691.8
4821.6
4123.6
4027.4
4365.2
4333.6
4930
5053
5031.4
5342
5191.4
4852.2
4675.6
4689.2
3809.4
4054.2
4409.6
4210.2
4566.4
4907
5021.8
5215.2
4933.6
5197.8
4734.6
4681.8
4172
4037.8
4462.6
4282.6
4962.4
4969.2
5214.6
5416.8
4764.2
5326.2
4545.4
4797.2
4259
4117
4469.2
4203.2
5033.8
4883
5361.6
5044.6
5005.6
5382
4565.4
4825
4290.2
3933.6
4177.6
3949.4
4492.6
4894.2
5224.4
5071

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299788&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299788&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299788&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center






ParameterEstimated ValueStandard Deviation
mean4825.6507936507945.5646297547657
standard deviation511.46170049261632.2190586818492

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 4825.65079365079 & 45.5646297547657 \tabularnewline
standard deviation & 511.461700492616 & 32.2190586818492 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299788&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]4825.65079365079[/C][C]45.5646297547657[/C][/ROW]
[ROW][C]standard deviation[/C][C]511.461700492616[/C][C]32.2190586818492[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299788&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299788&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:

ParameterEstimated ValueStandard Deviation
mean4825.6507936507945.5646297547657
standard deviation511.46170049261632.2190586818492


Figures (Output of Computation)

Input Parameters & R Code

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')