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The regression line is then drawn to best fit the scatter plot. .The predictions of y-values for given x-values are obtained by substituting the x-values into the regression equation.
The regression equation is determined using the least squares method and represents the relationship between the given variables. A scatter plot can be drawn to visualize this relationship and the regression line is drawn to best fit this scatter plot. Predictions can be made by substitifying given x-values into the regression equation. In statistics, regression is used to understand the relationship between variables by estimating the average value of the dependent variable when the independent variables are fixed. The regression equation represents this relationship mathematically. To find the regression equation, we typically use the least squares method. This minimizes the sum of the squared residuals, resulting in the equation of the form y = mx + c, where m is the slope of the line (the average change in y for each one-unit change in x), and c is the y-intercept (the estimated y-value when x = 0). A scatter plot can help you see the relationship between the variables. This involves plotting the given data pairs on a graph, with x-values on the horizontal axis and y-values on the vertical axis.
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