Regression and Correlation

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What does regression allow?
Allows Prediction of Y on the basis of X
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What is correlation?
Measures the strength of relationship between X and Y
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Pearsons
Interval or ratio
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Spearman's Rho
Ordinal + Ordinal
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Kendall's Tau
Ordinal and Ordinal
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Phi
True Dichotomy and True Dichotomy
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Point Biseral
True dichotomy and interval or ratio
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Venn Diagram
Size of circles represent variance of varibles
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What do overlapping circles denote?
Correlated variables
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What is Partial correlation?
What is the relationship between 2 variables once the effect of the other variables has been removed
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Multiple Regression
Y= B0 + B1X1 + B2X2 + BpXp
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Simultaneous
No Priori model, Enter all IVs at once
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Stepwise
Not a priori model, computer chooses on statistical ground, chance effects
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Hierarchical
Theoretically sound, sequence of entry
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Outliers
Cooks distance of 1 or greater
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Heteroscedasity
One variable is skewed or the relationship is non-linear
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Singularity
Redundancy, one variable combination of 2 or more other variables
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Multi-collinearity
Variables are highly correlated
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medium size effect
Multiple Correlations: N>50+8*m
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Simple linear regression
N>104+M
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Other cards in this set

Card 2

Front

What is correlation?

Back

Measures the strength of relationship between X and Y

Card 3

Front

Pearsons

Back

Preview of the front of card 3

Card 4

Front

Spearman's Rho

Back

Preview of the front of card 4

Card 5

Front

Kendall's Tau

Back

Preview of the front of card 5
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