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Author's title

Author

*Unverified author*

R Software Module

Ian.Hollidayrwasp_Simple Regression Y ~ X.wasp

Title produced by software

Simple Linear Regression

Date of computation

Tue, 04 May 2010 13:20:38 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/04/t1272979271l2tua3quba4bo26.htm/, Retrieved Tue, 30 Apr 2024 19:48:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75331, Retrieved Tue, 30 Apr 2024 19:48:04 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

156

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Simple Linear Regression] [PY2224 Mock Exam ...] [2010-04-28 07:33:16] [98fd0e87c3eb04e0cc2efde01dbafab6]
-    D  [Simple Linear Regression] [PY2224 May Mock E...] [2010-04-30 11:33:27] [98fd0e87c3eb04e0cc2efde01dbafab6]
-         [Simple Linear Regression] [PY2224 May Mock E...] [2010-04-30 11:37:32] [98fd0e87c3eb04e0cc2efde01dbafab6]
-    D        [Simple Linear Regression] [] [2010-05-04 13:20:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

1.6	 -41.0
1.8	 55.0
5.2	 30.0
4.1	 0.0
0.4	 17.0
2.7	 -61.0
2.4	 27.0
2.6          1
-67
80
-70
41
-37
0
7
-50
74
79
56
18
4
15
69
-6
32
57
59
68
-39
8
-349
169
51
43
58

2.4
7.2
3.7
8.4
1.5
8.0
0.0
7.1
2.8
8.2
2.3
5.0
5.9
6.2
3.6
1.6
3.2
2.6
1.6
5.8
2.8
1.2
-1.5
7.8
2.5
9.6
7.4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	67.202.21.85 @ 67.202.21.85
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.
R Engine error message	Error in as.vector(data) : element 16 is empty; the part of the args list of 'list' being evaluated was: (1.6, -41, 1.8, 55, 5.2, 30, 4.1, 0, 0.4, 17, 2.7, -61, 2.4, 27, 2.6, , 1, -67, 80, -70, 41, -37, 0, 7, -50, 74, 79, 56, 18, 4, 15, 69, -6, 32, 57, 59, 68, -39, 8, -349, 169, 51, 43, 58, 2.4, 7.2, 3.7, 8.4, 1.5, 8, 0, 7.1, 2.8, 8.2, 2.3, 5, 5.9, 6.2, 3.6, 1.6, 3.2, 2.6, 1.6, 5.8, 2.8, 1.2, -1.5, 7.8, 2.5, 9.6, 7.4) Calls: array -> as.vector Execution halted

\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 & 67.202.21.85 @ 67.202.21.85 \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
R Engine error message & Error in as.vector(data) : element 16 is empty;
   the part of the args list of 'list' being evaluated was:
   (1.6, -41, 1.8, 55, 5.2, 30, 4.1, 0, 0.4, 17, 2.7, -61, 2.4, 27, 2.6, , 1, -67, 80, -70, 41, -37, 0, 7, -50, 74, 79, 56, 18, 4, 15, 69, -6, 32, 57, 59, 68, -39, 8, -349, 169, 51, 43, 58, 2.4, 7.2, 3.7, 8.4, 1.5, 8, 0, 7.1, 2.8, 8.2, 2.3, 5, 5.9, 6.2, 3.6, 1.6, 3.2, 2.6, 1.6, 5.8, 2.8, 1.2, -1.5, 7.8, 2.5, 9.6, 7.4)
Calls: array -> as.vector
Execution halted
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75331&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]67.202.21.85 @ 67.202.21.85[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[ROW][C]R Engine error message[/C][C]Error in as.vector(data) : element 16 is empty;
   the part of the args list of 'list' being evaluated was:
   (1.6, -41, 1.8, 55, 5.2, 30, 4.1, 0, 0.4, 17, 2.7, -61, 2.4, 27, 2.6, , 1, -67, 80, -70, 41, -37, 0, 7, -50, 74, 79, 56, 18, 4, 15, 69, -6, 32, 57, 59, 68, -39, 8, -349, 169, 51, 43, 58, 2.4, 7.2, 3.7, 8.4, 1.5, 8, 0, 7.1, 2.8, 8.2, 2.3, 5, 5.9, 6.2, 3.6, 1.6, 3.2, 2.6, 1.6, 5.8, 2.8, 1.2, -1.5, 7.8, 2.5, 9.6, 7.4)
Calls: array -> as.vector
Execution halted
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75331&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75331&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 Output	view raw output of R engine
Computing time	1 seconds
R Server	67.202.21.85 @ 67.202.21.85
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.
R Engine error message	Error in as.vector(data) : element 16 is empty; the part of the args list of 'list' being evaluated was: (1.6, -41, 1.8, 55, 5.2, 30, 4.1, 0, 0.4, 17, 2.7, -61, 2.4, 27, 2.6, , 1, -67, 80, -70, 41, -37, 0, 7, -50, 74, 79, 56, 18, 4, 15, 69, -6, 32, 57, 59, 68, -39, 8, -349, 169, 51, 43, 58, 2.4, 7.2, 3.7, 8.4, 1.5, 8, 0, 7.1, 2.8, 8.2, 2.3, 5, 5.9, 6.2, 3.6, 1.6, 3.2, 2.6, 1.6, 5.8, 2.8, 1.2, -1.5, 7.8, 2.5, 9.6, 7.4) Calls: array -> as.vector Execution halted

Parameters (Session):

par1 = 2 ; par2 = 1 ; par3 = TRUE ;

Parameters (R input):

par1 = 2 ; par2 = 1 ; par3 = TRUE ;

R code (references can be found in the software module):

cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
xdf<-data.frame(t(y))
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
xdf <- data.frame(xdf[[cat1]], xdf[[cat2]])
names(xdf)<-c('Y', 'X')
if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) )
sumlmxdf<-summary(lmxdf)
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
nc <- ncol(sumlmxdf$'coefficients')
nr <- nrow(sumlmxdf$'coefficients')
a<-table.row.start(a)
a<-table.element(a,'Linear Regression Model', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],nc+1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'coefficients:',1,TRUE)
a<-table.element(a, ' ',nc,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',1,TRUE)
for(i in 1 : nc){
a<-table.element(a, dimnames(sumlmxdf$'coefficients')[[2]][i],1,TRUE)
}#end header
a<-table.row.end(a)
for(i in 1: nr){
a<-table.element(a,dimnames(sumlmxdf$'coefficients')[[1]][i] ,1,TRUE)
for(j in 1 : nc){
a<-table.element(a, round(sumlmxdf$coefficients[i, j], digits=3), 1 ,FALSE)
}# end cols
a<-table.row.end(a)
} #end rows
a<-table.row.start(a)
a<-table.element(a, '- - - ',1,TRUE)
a<-table.element(a, ' ',nc,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Std. Err. ',1,TRUE)
a<-table.element(a, paste(round(sumlmxdf$'sigma', digits=3), ' on ', sumlmxdf$'df'[2], 'df') ,nc, FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R-sq. ',1,TRUE)
a<-table.element(a, round(sumlmxdf$'r.squared', digits=3) ,nc, FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-sq. ',1,TRUE)
a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',1,TRUE)
a<-table.element(a, 'Df',1,TRUE)
a<-table.element(a, 'Sum Sq',1,TRUE)
a<-table.element(a, 'Mean Sq',1,TRUE)
a<-table.element(a, 'F value',1,TRUE)
a<-table.element(a, 'Pr(>F)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,1,TRUE)
a<-table.element(a, anova.xdf$Df[1])
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3))
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3))
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3))
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',1,TRUE)
a<-table.element(a, anova.xdf$Df[2])
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3))
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3))
a<-table.element(a, ' ')
a<-table.element(a, ' ')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='regressionplot.png')
plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution')
if(intercept == TRUE) abline(coef(lmxdf), col='red')
if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red')
dev.off()
library(car)
bitmap(file='residualsQQplot.png')
qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit')
dev.off()
bitmap(file='residualsplot.png')
plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit')
dev.off()

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code