| Tijdreeks A - Stap 26 | *Unverified author* | R Software Module: /rwasp_smp.wasp (opens new window with default values) | Title produced by software: Standard Deviation-Mean Plot | Date of computation: Wed, 11 Aug 2010 13:23:20 +0000 | | Cite this page as follows: | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c.htm/, Retrieved Wed, 11 Aug 2010 15:24:07 +0200 | | BibTeX entries for LaTeX users: | @Manual{KEY,
author = {{YOUR NAME}},
publisher = {Office for Research Development and Education},
title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c.htm/},
year = {2010},
}
@Manual{R,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2010},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}
| | Original text written by user: | | | IsPrivate? | No (this computation is public) | | User-defined keywords: | Jacobs Jeff | | Dataseries X: | » Textbox « » Textfile « » CSV « | 130
129
128
126
146
145
130
120
121
121
122
124
123
125
120
124
146
149
138
133
135
149
146
141
139
141
138
139
166
179
167
154
151
162
148
143
145
143
148
139
169
186
174
161
151
158
144
135
139
137
149
136
169
185
177
164
145
147
142
126
130
136
139
120
151
166
156
150
141
141
130
110
110
123
133
108
136
148
146
142
132
128
116
90
94
112
130
106
124
139
140
129
113
110
102
78
79
94
121
99
126
137
141
119
96
96
88
64
66
92
120
101
135
146
149
134
101
100
91
70 | | Output produced by software: |
Standard Deviation-Mean Plot | Section | Mean | Standard Deviation | Range | 1 | 128.5 | 8.72301032275608 | 26 | 2 | 135.75 | 10.7291023093098 | 29 | 3 | 152.25 | 13.5050495606778 | 41 | 4 | 154.416666666667 | 15.5063525594180 | 51 | 5 | 151.333333333333 | 18.2175406649412 | 59 | 6 | 139.166666666667 | 15.5612183055028 | 56 | 7 | 126 | 17.3572096626367 | 58 | 8 | 114.75 | 18.5870189306213 | 62 | 9 | 105 | 23.6988684041320 | 77 | 10 | 108.75 | 27.9321417985543 | 83 |
Regression: S.E.(k) = alpha + beta * Mean(k) | alpha | 41.3970300481064 | beta | -0.185538183493773 | S.D. | 0.0896744827297925 | T-STAT | -2.06901872021763 | p-value | 0.072339298003533 |
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) | alpha | 9.0512043180526 | beta | -1.28743754811647 | S.D. | 0.736264850466333 | T-STAT | -1.74860656094208 | p-value | 0.118483677000635 | Lambda | 2.28743754811647 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c/1jlph1281532996.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c/1jlph1281532996.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c/2jlph1281532996.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Aug/11/t1281533047ygse8oxhkr7xj5c/2jlph1281532996.ps (open in new window) |
| | Parameters (Session): | par1 = 12 ; | | Parameters (R input): | par1 = 12 ; | | R code (references can be found in the software module): | par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
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,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
| |
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