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Use this least squares regression line calculator to fit a straight line to your data points using the least square method.
The Least Squares Regression Calculator will return the slope of the line and the y-intercept. It will also generate an R-squared statistic, which evaluates how closely variation in the independent variable matches variation in the dependent variable (the outcome).
Find the least squares regression line for the data set as follows: {(2, 9), (5, 7), (8, 8), (9, 2)}. Also, work for the estimated value of y for the value of X to be 2 and 3.
The ordinary least squares method chooses the line parameters that minimize the sum of squares of the differences between the observed dependent variables (Y) and the estimated value by the linear regression (Ŷ).
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This simple linear regression calculator uses the least squares method to find the line of best fit for a set of paired data, allowing you to estimate the value of a dependent variable (Y) from a given independent variable (X).
Least Squares Calculator. Least Squares Regression is a way of finding a straight line that best fits the data, called the "Line of Best Fit". Enter your data as (x, y) pairs, and find the equation of a line that best fits the data.
Linear regression is a statistical method used to model the relationship between a dependent variable (Y) and one independent variable (X) by fitting a linear equation to observed data. The regression line equation is represented as: Y = b 0 + b 1 X. Where: Y = Dependent variable. X = Independent variable. b 0 = Intercept of the regression line.
Linear regression calculators determine the line-of-best-fit by minimizing the sum of squared error terms (the squared difference between the data points and the line). The calculator above will graph and output a simple linear regression model for you, along with testing the relationship and the model equation.
Use this Linear Regression Calculator to find out the equation of the regression line along with the linear correlation coefficient. It also produces the scatter plot with the line of best fit.