Asked by Narendrakumar Chowdary on Jun 02, 2024
Verified
The least squares method for determining the best fit minimizes:
A) total variation in the dependent variable
B) sum of squares for error
C) sum of squares for regression
D) sum of squares for the x values
E) all of these
Least Squares
A mathematical method used to find the best-fitting line or curve to a given set of data points by minimizing the sum of the squares of the differences between the observed and predicted values.
- Understand the significance of the sum of squares error within regression analysis.
Verified Answer
JC
Joshua ChungJun 04, 2024
Final Answer :
B
Explanation :
The least squares method for determining the best fit minimizes the sum of squares for error, which represents the distance between the actual data points and the predicted values. Minimizing this value ensures that the predicted values are as close to the actual data points as possible, making it the best choice for determining the best fit.
Learning Objectives
- Understand the significance of the sum of squares error within regression analysis.