Home » date » 2010 » May » 17 »

opgave8oef3

*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: Mon, 17 May 2010 09:58:15 +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/May/17/t127409073842em232466mingu.htm/, Retrieved Mon, 17 May 2010 12:05:40 +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/May/17/t127409073842em232466mingu.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:
KDGP2W83
 
Dataseries X:
» Textbox « » Textfile « » CSV «
196.9 192.1 201.8 186.9 218 214.4 227.5 204.1 225.8 223.7 244.7 243.9 257.3 234.5 251.4 243.8 247.4 245.3 262.5 270 259.9 262.2 244.9 249.3 268.2 231.2 264.3 252.7 275.5 261.5 275.5 272.3 268.6 270.4 267.7 275 272.6 248.6 279.4 270.5 292.8 297.8 296.8 290.9 282.8 312.8 303.2 301.4 289.8 279.6 302.2 299.1 319.7 310.9 315.2 338.5 315.6 321.2 318.5 342.7 261.4 287 331.5 326.9 338.6 337 358.4 344.5 345.7 344.1 317.4 354.5 345.2 314.1 352.5 361.2 365.9 332.5 364 359.1 345.6 366.9 370.2 359.9 366.6 336.3 368.5 374.2 384.3 358.9 407.7 433.3 404.7 392.7 409.7 416.5 414.3 404.3 421.4 372.6 404.7 420.2 438.4 449.1 445.8 413.8 420.5 442.3 438.9 394.5 416.8 402.9 424.5 432.3 484.1 492.7 496.3 471.9 491.2 512.9 482.4 407.9 448.5 431.1 498.8 497.1 517.1 487.7 512.5 550.1 532.5 524.1 515.7 461 529.3 467.4 559.8 536.5 531.9 546.5 547.4 536.1 482.8 551 532.9 484.1 554.8 537 558 5 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework
error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.


Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1194.4256.3913352804141614.9
22169.6681608040688623.4
3234.52511.324420514975621
4246.759.8605273692637822.8
5256.311.921129700382124.7
6254.0758.305169073133517.3
7254.116.625482449140137
8271.26.6402811185471214
9270.4253.257.30000000000001
10267.77513.335760195804430.8
11294.5753.266369034060116.90000000000003
12300.0512.541531007018230
13292.67510.185406226557722.6000000000000
14321.07512.159598403456227.6
15324.512.346929442848027.1000000000000
16301.733.482632313882870.1
17344.6259.7332334469760421.4000000000000
18340.42516.016527921702237.1
19343.2520.504389773899647.1
20355.37515.516738274091833.4
21360.6510.913752791776124.6000000000000
22361.417.042104721346337.9
23396.0531.840592540550174.4
24405.910.041248262375923.8
25403.1521.540736601456648.8
26428.119.638906962116544.4
27430.615.834350844498432
28413.27519.401095329903444.4
29458.434.963790793715068.2
30493.07516.885175944202341
31442.47531.385386726946774.5
32500.17512.294002602895529.4000000000000
33529.815.823611050157537.6
34493.3534.214275772938268.3
35543.67512.357555044047627.9
36529.32531.659582540941268.2
37527.230.264941213666170.7
38532.72529.735654804740255.7
39565.427.243959575167057.8
40578.139.301993164045494.1
41581.921.291469340246744.5
42594.12524.491137852973256.8000000000001
43530.72534.384916751389782.2
44592.47517.525671646663635.3000000000001
45582.1516.772497329457736.1999999999999
46550.87556.0184716559339121
47568.37548.0011371393081113.4
48564.935.30561806096483.9
49502.9518.091342312461738.2
50553.655.532633048806134.9
51626.821.427085662777440.2000000000000
52600.82536.927620647242785.7
53627.67597.2408821775423206.3
54692.123.025637884757949.1999999999999
55633.37573.1785203002447161.7
56592.8569.7401605963164128.4
57712.560.1117293046873126.8
58667.52522.778699845835552.1
5964173.7295508372773161.9
60652.3545.0614765255941106.9
61648.07552.6324598829784121.8
62684.4541.371286338876899.2
63610.9538.182936852299281.1
64611.5556.6006183711803115.2
65615.0527.122008283557063.3
66601.57534.191360994652880
67629.97549.6467101964807101.1
68644.47571.3917070347343155.3
69622.733.218769794600667.9000000000001
70640.82532.387073038482569.5
71674.97528.983256660814868.8
72715.533.030289129827574.4
73644.4596.5605336908753234.5
74621.175110.976074748869247.3
75632.616.072958657322639
76682.438.843789722425494
77679.861.3942451157544140.2
78546.3526.223844111800257
79597.37571.4051060265768164.2
80603.439.382991252569994.5
81391.92525.410283351430845.6
82403.418.099723754798040.8
83469.7554.0393375236966129
84511.2514.056433876817233
85501.535.763109484495371
86543.7514.908051515875633
87531.526.095976701399858
88498.2536.123630308520686
89568.526.210684844162354
90577.511.902380714238128
9154735.953673896650288
9256229.743346594939065
93566.7517.461863207191542
9450240.340219797781680
95527.7533.480093588081173
96502.551.1891915674914117
97491.2575.5183
9853536.064756572957381
99573.510.344080432788624
10054324.138489320308952
101561.536.28130831893179
102579.2527.657126869338259
10353054.9120508935273125
104560.2545.050897142380396
105576.2517.114808402861739
106455.531.160872901765872
107529.584.3267454607374150
108519.2570.2204860896496153
109542.529.894258088580660
11052536.450880190561580
111547.757.2284161474004815
112563.2527.366341857593459
113617.2515.107944929738135


Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-12.8435610766660
beta0.0884094820589686
S.D.0.0135600340235821
T-STAT6.51985694912095
p-value2.15117889285918e-09


Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-6.1503866250009
beta1.51773617505999
S.D.0.167796682868188
T-STAT9.04509045779075
p-value5.61907124891875e-15
Lambda-0.517736175059991
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/May/17/t127409073842em232466mingu/1qcof1274090293.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/17/t127409073842em232466mingu/1qcof1274090293.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/17/t127409073842em232466mingu/2qcof1274090293.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/17/t127409073842em232466mingu/2qcof1274090293.ps (open in new window)


 
Parameters (Session):
par1 = 4 ;
 
Parameters (R input):
par1 = 4 ;
 
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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Software written by Ed van Stee & Patrick Wessa


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