Fundamental Concepts - Multiple Regression
13 important questions on Fundamental Concepts - Multiple Regression
What are zero-order correlations?
How is Y in MR also called?
Why is OLS a partial-information method?
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What is the multiple correlation between the predictors and the criterion?
What does it mean that OLS "capatilizes on chance"?
(2). It is hard to find similair values for B1, B2 and A in a replication of the sample.
What can you do to downward the adjusted R² values?
What are the assumptions of Multiple Regression? (MR)
(2). Homoscedasticity (normal distribution with uniform variances)
(3). No measurement error
(4). Omitted predictors are not correlated with the measured or used predictors.
What is the specification error in MR?
What is negative suppression?
What is classical suppresion?
What is reciprocal suppresion?
What are the two ways to enter predictors into the equation?
2. Sequantial entry (in steps)
How can the entry order for a MR equation be determined?
2. Empirical (statistical) --> Stepwise / Forward inclusion / Backward Elimination
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