Math  /  Data & Statistics

QuestionThe least squares method minimizes which of the following? All of the above SST SSE SSR

Studdy Solution

STEP 1

1. We are considering the context of linear regression.
2. The least squares method is used to find the best-fitting line through a set of data points by minimizing the sum of squared differences.

STEP 2

1. Define the components of total variability in regression.
2. Identify which component the least squares method minimizes.

STEP 3

Define the components of total variability:
- SST (Total Sum of Squares): Measures the total variability in the dependent variable. - SSR (Regression Sum of Squares): Measures the variability explained by the regression model. - SSE (Error Sum of Squares): Measures the variability not explained by the regression model, i.e., the error or residuals.

STEP 4

Identify which component the least squares method minimizes:
The least squares method minimizes the SSE (Error Sum of Squares), which is the sum of the squared differences between the observed values and the values predicted by the model.
The least squares method minimizes:
SSE \boxed{\text{SSE}}

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