What are the assumptions made in simple linear regression?
- Homogeneity, normality, and symmetry
- Independence, homogeneity, and linearity
- Linearity, homoscedasticity, and normality
- Symmetry, linearity, and independence
The assumptions made in simple linear regression include linearity (the relationship between the independent and dependent variables is linear), homoscedasticity (the variance of the residuals is constant across all levels of the independent variable), and normality (the residuals are normally distributed).
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