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![> attach(dat)
> datS<-subset(Stockholm,År>=1994&År<2009)
> yearS<-subset(År,År>=1994&År<2009)
> datS
[1] 39 102 212 493 531 1312 1775 2552 3128 3736 4207 4643 5731 5232 5196
> yearS
[1] 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
> regrS<-lm(datS~yearS)
> summary(regrS)
Call:
lm(formula = y ~ x)
Residuals:
Min 1Q Median 3Q Max
-686.9 -313.0 -40.6 233.3 847.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -914315.62 53131.05 -17.21 2.51e-10 ***
x 458.22 26.55 17.26 2.42e-10 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 444.3 on 13 degrees of freedom
Multiple R-squared: 0.9582, Adjusted R-squared: 0.955
F-statistic: 297.8 on 1 and 13 DF, p-value: 2.421e-10
Haha, kolla det p-värdet! Tror jag är något på spåren här.](http://cdn08.dayviews.com/75/_u5/_u3/_u0/_u6/_u8/u530680/28850_1268054627/_attach_dat_datS_subset_Stockholm_Ar_1994_Ar_2009_yearS_subset_Ar_Ar_1994_Ar_2009_datS_1_39_102_212.jpg)
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> attach(dat)
> datS<-subset(Stockholm,År>=1994&År<2009)
> yearS<-subset(År,År>=1994&År<2009)
> datS
[1] 39 102 212 493 531 1312 1775 2552 3128 3736 4207 4643 5731 5232 5196
> yearS
[1] 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
> regrS<-lm(datS~yearS)
> summary(regrS)
Call:
lm(formula = y ~ x)
Residuals:
Min 1Q Median 3Q Max
-686.9 -313.0 -40.6 233.3 847.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -914315.62 53131.05 -17.21 2.51e-10 ***
x 458.22 26.55 17.26 2.42e-10 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 444.3 on 13 degrees of freedom
Multiple R-squared: 0.9582, Adjusted R-squared: 0.955
F-statistic: 297.8 on 1 and 13 DF, p-value: 2.421e-10
Haha, kolla det p-värdet! Tror jag är något på spåren här.
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