Entwurf

391  moderation

DUMMY
Veröffentlichungsdatum

2. Juli 2024

Schlüsselwörter

Aufgaben, Statistik, Prognose, Modellierung, R, Datenanalyse, Regression

391.1 Aufgabe

Gegeben sei das folgende lineare Modell.

library(tidyverse)
library(easystats)
library(rstanarm)
data(mariokart, package = "openintro")

mariokart_z <-
  mariokart |>
  standardise(select = c("wheels", "total_pr"))

model1 <- stan_glm(total_pr ~ wheels + stock_photo + wheels:stock_photo, data = mariokart_z)
## 
## SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
## Chain 1: 
## Chain 1: Gradient evaluation took 2e-05 seconds
## Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.2 seconds.
## Chain 1: Adjust your expectations accordingly!
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## Chain 1: 
## Chain 1:  Elapsed Time: 0.024 seconds (Warm-up)
## Chain 1:                0.029 seconds (Sampling)
## Chain 1:                0.053 seconds (Total)
## Chain 1: 
## 
## SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
## Chain 2: 
## Chain 2: Gradient evaluation took 6e-06 seconds
## Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.06 seconds.
## Chain 2: Adjust your expectations accordingly!
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## Chain 2:  Elapsed Time: 0.023 seconds (Warm-up)
## Chain 2:                0.029 seconds (Sampling)
## Chain 2:                0.052 seconds (Total)
## Chain 2: 
## 
## SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
## Chain 3: 
## Chain 3: Gradient evaluation took 4e-06 seconds
## Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.04 seconds.
## Chain 3: Adjust your expectations accordingly!
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## Chain 3:  Elapsed Time: 0.022 seconds (Warm-up)
## Chain 3:                0.029 seconds (Sampling)
## Chain 3:                0.051 seconds (Total)
## Chain 3: 
## 
## SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
## Chain 4: 
## Chain 4: Gradient evaluation took 5e-06 seconds
## Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.05 seconds.
## Chain 4: Adjust your expectations accordingly!
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## Chain 4:  Elapsed Time: 0.023 seconds (Warm-up)
## Chain 4:                0.029 seconds (Sampling)
## Chain 4:                0.052 seconds (Total)
## Chain 4:

Hier sind die Ergebnisse des Modells:

parameters(model1)
plot(parameters(model1))

Welche Aussage zum Modell model1 ist korrekt?

  1. Liegen Stock-Photos bei, ist ein höheres Preis zu erwarten.
  2. Es liegt ein Interaktionseffekt vor und zwar so, dass der Effekt von wheels negativ ist, wenn Stock-Photos vorliegen.
  3. Es liegt ein Interaktionseffekt vor und zwar so, dass der Effekt von wheels positiv ist, wenn Stock-Photos vorliegen.
  4. Es kann nicht ausgeschlossen werden, dass kein Interaktionseffekt vorliegt, da die Null im 95%-CI enthalten ist.
  5. wheels hat einen negativen Effekt, wobei die Null aus dem 95% CI ausgeschlossen ist.

Hinweise:

  • Beachten Sie die üblichen Hinweise des Datenwerks.

391.2 Lösung

D