Which of the following statements is true about the Least Squares method of regression? The fitted model will have the smallest possible value of SSE The fitted model will have SSR = 0 The fitted model will have the smallest possible values of SST Least squares can only be used for simple linear regression

Which of the following statements is true about the Least Squares method of regression? The fitted model will have the smallest possible value of SSE The fitted model will have SSR = 0 The fitted model will have the smallest possible values of SST Least squares can only be used for simple linear regression

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Which of the following statements is true about the Least Squares method of regression?
The fitted model will have the smallest possible value of SSE
The fitted model will have SSR = 0
The fitted model will have the smallest possible values of SST
Least squares can only be used for simple linear regression

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