CFA® Level I Quantitative Methods - Simple Linear Regression (ANOVA, SEE, R2)

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ANOVA (Analysis of Variance) is a statistical test used to determine if there is a significant difference between the means of two or more groups. In simple linear regression, ANOVA is used to determine if the regression model is significantly better than just predicting the mean of the dependent variable.
SEE (Standard Error of the Estimate) is a measure of the accuracy of the regression model. It represents the average distance that the observed values fall from the regression line. A smaller SEE indicates a better fitting model.
R-squared is a measure of how well the regression model fits the data. It represents the percentage of the variance in the dependent variable that is explained by the independent variable. A higher R-squared value indicates a better fitting model.

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[@MegawatiMegawati-z2j]

Thanks for sharing this video, it's very helpful for learning SLR.

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[@anshugupta1199]

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[@vidhibangur5867]

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[@ahsanchowdhury2193]

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[@travisbradfield1311]

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[@gamingcastle2296]

Where is part 1?

[@thanhomerae]

still couldn't understand what it is talking about....