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Regression - Coggle Diagram
Regression
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OLS regression model
Used to quantify causality between regressors and regressand.
Types of causalities: linear and non-linear relationships.
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(Adjusted) coefficient of determination (R~2, R2)
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Introduction
Dependence technique: examines the linear relationship between a dependent variable and one or more independent variables.
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A deterministic model represents a linear relationship between the variables, but it may not be plausible in many cases.
A probabilistic model incorporates a random error term to account for the variability in the dependent variable.
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Sample size is important consideration, larger samples are generally preferred for more reliable results.
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Cross-validation
splitting the data into estimation (50-90% total sample) and validation samples, estimating the model on the estimation sample, then assessing the agreement and performance on the validation sample.
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When in doubt, include irrelevant variables
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minimizing the sum of squared residuals through methods such as Ordinary Least Squares (OLS) regression
Dummy variable
Nominal and ordinal independent variables can be dichotomized using dummy variables. 1 category chosen as the reference group for comparison.