| Spaargeld NL vs Leningen NL | *The author of this computation has been verified* | R Software Module: /rwasp_linear_regression.wasp (opens new window with default values) | Title produced by software: Linear Regression Graphical Model Validation | Date of computation: Tue, 21 Dec 2010 14:30:35 +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/Dec/21/t1292942150bpeg3gpxpbwqx6k.htm/, Retrieved Tue, 21 Dec 2010 15:35:50 +0100 | | 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/Dec/21/t1292942150bpeg3gpxpbwqx6k.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: | Spaargeld Huishoudens NL vs Uitgegeven Leningen Banken NL | | Dataseries X: | » Textbox « » Textfile « » CSV « | 143827
145191
146832
148577
149873
151847
153252
154292
155657
156523
156416
156693
160312
160438
160882
161668
164391
168556
169738
170387
171294
172202
172651
172770
178366
180014
181067
182586
184957
186417
188599
189490
190264
191221
191110
190674
195438
196393
197172
198760
200945
203845
204613
205487
206100
206315
206291
207801
211653
211325
211893
212056
214696
217455
218884
219816
219984
219062
218550
218179
222218
222196
223393
223292
226236
228831
228745
229140
229270
229359
230006
228810
232677
232961
234629
235660
240024
243554
244368
244356
245126
246321
246797
246735
251083
251786
252732
255051
259022
261698
263891
265247
262228
263429
264305
266371
273248
275472
278146
279506
283991
286794
288703
289285
288869
286942
285833
284095
289229
289389
290793
291454
294733
293853
294056
293982
293075
292391 | | Dataseries Y: | » Textbox « » Textfile « » CSV « | 829461
837669
854793
850092
848783
846150
828543
830389
848989
841106
854616
832714
839290
840572
869186
856979
872126
868281
862455
881177
886924
886842
916407
890606
900409
920169
922871
920004
945772
937507
941691
958256
963509
970266
972853
982168
999892
1002099
1017611
1029782
1047956
1047689
1060054
1067078
1072366
1081823
1087601
1089905
1116316
1111355
1124250
1140597
1151683
1137532
967532
972994
999207
1007982
1015892
994850
987503
986743
1020674
1024067
1040444
1019081
1027828
1021010
1025563
1044756
1062545
1070425
1100087
1093596
1109143
1113855
1129275
1131996
1144103
1167830
1153194
1175008
1175805
1173456
1187498
1202958
1206229
1249533
1279743
1283496
1282942
1284739
1337169
1314087
1306144
1200391
1265445
1259329
1219342
1227626
1232874
1241046
1244172
1237838
1212801
1234237
1224699
1237432
1248847
1256543
1252434
1265176
1314670
1299329
1216744
1225275
1193478
1207226 | | Output produced by software: |
Simple Linear Regression | Statistics | Estimate | S.D. | T-STAT (H0: coeff=0) | P-value (two-sided) | constant term | 371942.193319744 | 23555.4325175870 | 15.7900812494971 | 0 | slope | 3.13018153858995 | 0.104252399872365 | 30.025031005734 | 0 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/1wt0k1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/1wt0k1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/2wt0k1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/2wt0k1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/372zn1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/372zn1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/45fof1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/45fof1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/55fof1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/55fof1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/6blgb1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/6blgb1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/7blgb1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/7blgb1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/83ufw1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/83ufw1292941830.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/93ufw1292941830.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292942150bpeg3gpxpbwqx6k/93ufw1292941830.ps (open in new window) |
| | Parameters (Session): | par1 = 0 ; | | Parameters (R input): | par1 = 0 ; | | R code (references can be found in the software module): | par1 <- as.numeric(par1)
library(lattice)
z <- as.data.frame(cbind(x,y))
m <- lm(y~x)
summary(m)
bitmap(file='test1.png')
plot(z,main='Scatterplot, lowess, and regression line')
lines(lowess(z),col='red')
abline(m)
grid()
dev.off()
bitmap(file='test2.png')
m2 <- lm(m$fitted.values ~ x)
summary(m2)
z2 <- as.data.frame(cbind(x,m$fitted.values))
names(z2) <- list('x','Fitted')
plot(z2,main='Scatterplot, lowess, and regression line')
lines(lowess(z2),col='red')
abline(m2)
grid()
dev.off()
bitmap(file='test3.png')
m3 <- lm(m$residuals ~ x)
summary(m3)
z3 <- as.data.frame(cbind(x,m$residuals))
names(z3) <- list('x','Residuals')
plot(z3,main='Scatterplot, lowess, and regression line')
lines(lowess(z3),col='red')
abline(m3)
grid()
dev.off()
bitmap(file='test4.png')
m4 <- lm(m$fitted.values ~ m$residuals)
summary(m4)
z4 <- as.data.frame(cbind(m$residuals,m$fitted.values))
names(z4) <- list('Residuals','Fitted')
plot(z4,main='Scatterplot, lowess, and regression line')
lines(lowess(z4),col='red')
abline(m4)
grid()
dev.off()
bitmap(file='test5.png')
myr <- as.ts(m$residuals)
z5 <- as.data.frame(cbind(lag(myr,1),myr))
names(z5) <- list('Lagged Residuals','Residuals')
plot(z5,main='Lag plot')
m5 <- lm(z5)
summary(m5)
abline(m5)
grid()
dev.off()
bitmap(file='test6.png')
hist(m$residuals,main='Residual Histogram',xlab='Residuals')
dev.off()
bitmap(file='test7.png')
if (par1 > 0)
{
densityplot(~m$residuals,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~m$residuals,col='black',main='Density Plot')
}
dev.off()
bitmap(file='test8.png')
acf(m$residuals,main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test9.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Simple Linear Regression',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistics',1,TRUE)
a<-table.element(a,'Estimate',1,TRUE)
a<-table.element(a,'S.D.',1,TRUE)
a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE)
a<-table.element(a,'P-value (two-sided)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'constant term',header=TRUE)
a<-table.element(a,m$coefficients[[1]])
sd <- sqrt(vcov(m)[1,1])
a<-table.element(a,sd)
tstat <- m$coefficients[[1]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'slope',header=TRUE)
a<-table.element(a,m$coefficients[[2]])
sd <- sqrt(vcov(m)[2,2])
a<-table.element(a,sd)
tstat <- m$coefficients[[2]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
| |
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