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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Reddy-Moores Data Boxplot V2.0.wasp
Title produced by softwareBoxplot and Trimmed Means
Date of computationFri, 01 Jun 2012 06:09:02 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jun/01/t1338545347ved4zresqprtmy4.htm/, Retrieved Thu, 02 May 2024 10:59:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168574, Retrieved Thu, 02 May 2024 10:59:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Simple Linear Regression] [Triglyceridge Reg...] [2011-07-07 15:11:49] [74be16979710d4c4e7c6647856088456]
- R     [Simple Linear Regression] [Triglyceride] [2012-05-04 19:33:41] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R       [Simple Linear Regression] [influence of leve...] [2012-06-01 08:56:32] [c14255f5a914c4d7aab5f6cd60318f9b]
- RMPD        [Boxplot and Trimmed Means] [] [2012-06-01 10:09:02] [0507bbe3d00274d9f4e781e2396a3b5a] [Current]
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Dataseries X:
50	148	47	148
50	160	55	150
52	152	51	150
47	150	45	152
39	157	41	153
52	159	52	153
45	157	45	153
52	158	51	155
44	157	44	155
55	160	55	155
59	159	59	155
53	158	50	155
50	158	49	155
53	161	54	158
51	161	52	158
54	160	55	158
75	162	75	158
63	160	64	158
56	160	53	158
59	157	55	158
53	162	52	158
51	156	51	158
58	161	51	159
63	163	59	159
56	163	57	159
52	163	57	160
58	166	60	160
54	164	53	160
60	162	59	160
57	163	59	160
57	162	56	160
56	165	57	160
47	163	47	160
45	163	45	160
53	164	51	160
53	162	53	160
52	163	53	160
47	162	47	160
48	163	44	160
51	163	50	160
54	161	54	160
63	165	59	160
56	162	56	160
52	164	52	161
64	164	62	161
50	166	50	161
56	161	56	161
56	163	58	161
62	164	61	161
166	57	56	163
56	165	57	163
64	165	63	163
55	165	54	163
61	165	60	163
60	167	55	163
55	164	55	163
59	166	55	163
62	168	62	163
55	165	55	163
62	166	61	163
53	165	55	163
57	167	55	164
76	170	76	165
76	167	77	165
64	168	64	165
65	166	66	165
62	168	62	165
50	166	50	165
71	166	71	165
56	166	54	165
68	165	69	165
53	165	53	165
50	169	50	165
64	166	64	165
76	167	77	165
75	169	76	165
69	167	73	165
55	165	55	165
57	168	58	165
54	169	58	165
57	167	56	165
66	166	66	165
76	169	75	165
66	170	67	165
59	164	59	165
58	169	54	166
54	171	59	168
63	169	61	168
64	172	62	168
63	170	62	168
62	168	64	168
60	172	55	168
75	172	70	169
78	173	75	169
68	171	68	169
65	171	64	170
61	170	61	170
66	173	70	170
68	169	63	170
74	169	73	170
57	173	58	170
71	177	71	170
55	168	56	170
56	170	56	170
70	173	68	170
70	173	67	170
61	170	61	170
61	175	61	171
69	174	69	171
62	175	61	171
79	179	79	171
55	174	57	171
64	171	66	171
59	172	58	171
65	176	64	172
65	175	66	173
79	173	76	173
54	174	56	173
62	175	63	173
68	174	68	173
70	173	70	173
89	173	86	173
70	175	75	174
69	172	68	174
68	177	70	175
71	178	71	175
75	178	73	175
64	176	65	175
88	178	86	175
85	179	82	175
71	180	76	175
80	178	76	175
66	173	66	175
53	169	52	175
62	178	66	175
63	178	63	175
78	178	77	175
68	178	68	175
83	177	84	175
66	175	68	175
81	178	82	175
80	176	78	175
74	175	71	175
54	176	55	176
119	180	124	178
80	178	80	178
65	178	66	178
71	178	68	178
90	181	91	178
79	177	81	178
67	179	67	179
77	182	77	180
69	186	73	180
101	183	100	180
78	183	80	180
73	183	74	180
69	182	70	180
69	180	71	180
76	183	75	180
83	180	80	180
83	184	83	181
103	185	101	182
82	182	85	183
69	183	70	183
59	182	61	183
84	184	86	183
84	183	90	183
96	184	94	183
88	184	86	183
92	187	101	185
102	185	107	185
97	189	98	185
88	189	87	185
87	185	89	185
90	188	91	185
65	187	67	188
85	191	83	188
96	191	95	188
88	185	93	188
76	197	75	200




\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Engine error message & 
Error in boxplot.default(split(mf[[response]], mf[-response]), ...) : 
  invalid first argument
Calls: boxplot -> boxplot.formula -> boxplot -> boxplot.default
In addition: Warning message:
In is.na(rows) : is.na() applied to non-(list or vector) of type 'NULL'
Execution halted
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=168574&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in boxplot.default(split(mf[[response]], mf[-response]), ...) : 
  invalid first argument
Calls: boxplot -> boxplot.formula -> boxplot -> boxplot.default
In addition: Warning message:
In is.na(rows) : is.na() applied to non-(list or vector) of type 'NULL'
Execution halted
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=168574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168574&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Engine error message
Error in boxplot.default(split(mf[[response]], mf[-response]), ...) : 
  invalid first argument
Calls: boxplot -> boxplot.formula -> boxplot -> boxplot.default
In addition: Warning message:
In is.na(rows) : is.na() applied to non-(list or vector) of type 'NULL'
Execution halted



Parameters (Session):
par1 = two.sided ; par2 = 1 ; par3 = 2 ;
Parameters (R input):
par1 = 3 ; par2 = TRUE ; par3 = 0 ; par4 = 1 ; par5 = 2 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) # colour
par2<- as.logical(par2) # notches
par3<-as.numeric(par3) # percentage trim
if(par3>45){par3<-45;warning('trim limited to 45%')}
if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')}
par4 <- as.numeric(par4) #factor column
par5 <- as.numeric(par5) # response column
x <- t(x)
x1<-as.numeric(x[,par5]) # response
f1<-as.character(x[,par4]) # factor
x2<-x1[f1=='no']
f2 <- f1[f1=='no']
lotrm<-as.integer(length(x2)*par3/100)
hitrm<-as.integer(length(x2)*(100-par3)/100)
srt<-order(x2,f2)
trmx1<-x2[srt[lotrm:hitrm]]
trmf1<-f2[srt[lotrm:hitrm]]
x3<-x1[f1=='yes']
f3 <- f1[f1=='yes']
lotrm<-as.integer(length(x3)*par3/100)
hitrm<-as.integer(length(x3)*(100-par3)/100)
srt<-order(x3,f3)
trmx2<-x3[srt[lotrm:hitrm]]
trmf2<-f3[srt[lotrm:hitrm]]
xtrm<-c(trmx1,trmx2)
ftrm<-c(trmf1,trmf2)
xtrm[1:6]
ftrm[1:6]
bitmap(file='test1.png')
r<-boxplot(xtrm~as.factor(ftrm), col=par1, notch=par2, main='Reddy and Moores Placements Data', xlab='Placement Student', ylab='Degree Grade')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('overview.htm','Boxplot statistics','Boxplot overview'),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Placement',1,TRUE)
a<-table.element(a,hyperlink('lower_whisker.htm','lower whisker','definition of lower whisker'),1,TRUE)
a<-table.element(a,hyperlink('lower_hinge.htm','lower hinge','definition of lower hinge'),1,TRUE)
a<-table.element(a,hyperlink('central_tendency.htm','median','definitions about measures of central tendency'),1,TRUE)
a<-table.element(a,hyperlink('upper_hinge.htm','upper hinge','definition of upper hinge'),1,TRUE)
a<-table.element(a,hyperlink('upper_whisker.htm','upper whisker','definition of upper whisker'),1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'no',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,1])
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'yes',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,2])
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
tr.mns<-tapply(x1,f1,mean, trim=par3/100)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('trimmed_mean.htm','Trimmed Mean Equation','Trimmed Mean'),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'No Placement')
a<-table.element(a,'Placement')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,tr.mns[1])
a<-table.element(a,tr.mns[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')