myPlotumit: Korrelationsplot für einfache Regression
In lillion/emittr: Hilfsfunktionen fuer die psychologische Forschung
Description
Usage
Arguments
Value
See Also
Examples
Description
dient nur Lernzwecken
Usage
1
Arguments
beta
data
Value
plot
See Also
lm
Examples
1
2
3
4
5
6
7
library(dplyr)
library(psych)
dfcov <- data_frame(punkte_intel=c(10,30,10,50,30,15),
punkte_klaus=c(10,19,30,50,60,20),dx=punkte_intel-mean(punkte_intel),
dy=punkte_klaus-mean(punkte_klaus),covZ=dx*dy,cov=covZ/(length(punkte_intel)-1))
library(manipulate)
manipulate(myPlotumit(beta,dfcov), beta = slider(-1, 1, step = 0.01))
lillion/emittr documentation built on May 10, 2020, 7:23 a.m.
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Description Usage Arguments Value See Also Examples
Description
dient nur Lernzwecken
Usage
1 |
Arguments
beta |
data |
Value
plot
See Also
lm
Examples
1 2 3 4 5 6 7 | library(dplyr)
library(psych)
dfcov <- data_frame(punkte_intel=c(10,30,10,50,30,15),
punkte_klaus=c(10,19,30,50,60,20),dx=punkte_intel-mean(punkte_intel),
dy=punkte_klaus-mean(punkte_klaus),covZ=dx*dy,cov=covZ/(length(punkte_intel)-1))
library(manipulate)
manipulate(myPlotumit(beta,dfcov), beta = slider(-1, 1, step = 0.01))
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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