Regression Flashcards

1
Q

What are the two common goals of regression?

A
  • explanatory modelling
  • predictive modelling
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2
Q

What is the main goal of regression?

A

identify and define the straight line that best represents the relationship between variables

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3
Q

What is linear regression?

A

a statistical technique where we model the best fitting straight line for a set of data

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4
Q

What is distance?

A

measures the amount of error (residual) between the line and the actual data

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5
Q

What is the least-squares solution?

A

aims to minimize error in prediction

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6
Q

What is the best-fitting regression line?

A

smallest SSresidual

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7
Q

What is the process of testing the significance of a regression equation?

A

analysis of regression

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8
Q

What happens during regression analysis?

A

the F ratio is used to assess the overall significance of linear regression model by comparing the fit of a full model to the fit of a reduced model

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9
Q

What is the numerator of the F-ratio?

A

MSregression which is the variance in the Y scores that is predicted by the regression equation

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10
Q

What does the MSregression measure?

A

measures systematic changes in Y that occur when the value of X increases or decreases

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11
Q

What is the denominator of the F-ratio?

A

MSresidual which is the unpredicted variance in the Y scores

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12
Q

What does the MSresidual measure?

A

measures the changes in Y that are independent of changes in X

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13
Q

What is R^2?

A

the proportion of variance in the dependent/outcome variable (Y) that can be explained by the independent/predictor variable (X)

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14
Q

What does SSresidual tell us?

A

how much of the variation in the DV our model did not explain

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15
Q

What does SStotal tell us?

A

how much variation there is in the dv

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16
Q

How do we assess the predictive ability of individual predictors?

A

t-test

17
Q

What does it mean the t-test is significant?

A

b predicts changes in the outcome variable

18
Q

What is simple linear regression?

A

models the predictive relationship between a dependent/outcome variable (Y) and one independent/predictor variable (X)

19
Q

What is multiple linear regression?

A

a model that predicts a dependent/outcome variable (Y) from multiple independent/predictor variables