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Samenvatting Experimenteel en Correlationeel onderzoek week 3 - Meervoudige lineaire regressie R92,69   Add to cart

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Samenvatting Experimenteel en Correlationeel onderzoek week 3 - Meervoudige lineaire regressie

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Samenvatting over de stof uit week 3 van Experimenteel en Correlationeel onderzoek, met als hoofdonderwerp: Meervoudige lineaire regressie.

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  • September 15, 2022
  • 4
  • 2019/2020
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Samenvatting week 3 Experimenteel en Correlationeel onderzoek

Deze week hebben we het over meervoudige lineaire regressie.  zie voor de
basis samenvatting week 2

(On)gestandaardiseerde meervoudige regressievergelijking opstellen o.b.v. SPSS-
uitvoer

Meervoudige lineaire regressie:
1 responsevariabele (y) + 2 of meer predictorvariabele (x 1, x2, x3)

Regressievergelijking steekproef: yˆ = b0 + b1x1 + b2x2 + ... + bpxp
Regressievergelijking populatie: µy = β0 + β1x1 + β2x2 + ... + βpxp


Voorbeeld:




Ongestandaardiseerde meervoudige regressievergelijking
Waardes uit de kolom B  Constant + Extraversion X1 + Emo-stability X2
Dus hier geldt: 2.494 + 0.352X1 + 0.174X2

Gestandaardiseerde meervoudige regressievergelijking:
Waardes uit de kolom Beta  Extraversion X1 + Emo-stability X2
Dus hier geldt: 0.276X1 + 0.196X2


Varianties van het regressiemodel
- Totale variantie (MSy) = SStotaal : dftotaal = SSy : dfy
Waarbij:
SSy =  (y - y )2

dfy = N -1

- Model variantie (MS ^y ) = SSmodel : dfmodel = SS ^y : df ^y
Waarbij:
SS ^y =  ( ^y - y )2

df ^y = p (aantal predictoren)

- Residuele/error/onverklaarde variantie (MSe) = SSerror : dferror = SSe :
dfe
Waarbij:
SSe =  (y- ^y )2  dit is ook wel de som van ei in het kwadraat

dfe = N-p-1
Proportie verklaarde variantie

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