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Determine relationship in Linear Regression

Determine relationship in Linear Regression

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Given that,

Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable.

For example, a modeler might want to relate the weights of individuals to their heights using a linear regression model.

A linear regression line has an equation of the form Y = a + bX, .

where X is the explanatory variable and Y is the dependent variable.

The slope of the line is b, and a is the intercept (the value of y when x = 0).

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