It can look like any algebraic equation.
of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com
The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.
on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line
It seems like your question is incomplete, as it only mentions "the equation for a regression line for the data set 3." To provide a meaningful answer, I would need more context about the data set or the specific regression line you're referring to. Please provide additional details so I can assist you better!
Yes.
of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com
If the regression is a perfect fit.
The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.
on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line
It seems like your question is incomplete, as it only mentions "the equation for a regression line for the data set 3." To provide a meaningful answer, I would need more context about the data set or the specific regression line you're referring to. Please provide additional details so I can assist you better!
Yes.
once an equation for a regression is derived it can be used to predict possible future
The symbol commonly used to represent regression is "β" (beta), which denotes the coefficients of the regression equation. In the context of simple linear regression, the equation is often expressed as ( y = β_0 + β_1x + ε ), where ( β_0 ) is the y-intercept, ( β_1 ) is the slope, and ( ε ) represents the error term. In multiple regression, additional coefficients (β values) correspond to each independent variable in the model.
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what is the equation of the regression line for the given data(Age, Number of Accidents) (16, 6605), (17, 8932), (18, 8506), (19, 7349), (20, 6458), (21, 5974)
No. It is an estimated equation that defines the best linear relationship between two variables (or their transforms). If the two variables, x and y were the coordinates of a circle, for example, any method for calculating the regression equation would fail hopelessly.
includes both positive and negative terms.