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  • https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./07%3A_Introduction_to_Linear_Regression/7.02%3A_Line_Fitting_Residuals_and_Correlation
    In this section, we examine criteria for identifying a linear model and introduce a new statistic, correlation.
  • https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Support_Course_for_Elementary_Statistics/Graphing_Points_and_Lines_in_Two_Dimensions/Finding_Residuals
    In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observe...In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observed value of y and  y based on the equation of the regression line.
  • https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/09%3A_Correlation_and_Regression/9.02%3A_Simple_Linear_Regression/9.2.02%3A_Residuals
    The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterp...The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterplot vertically as a yellow double-sided arrow to visually show the size of the residual. The mean square error is the variance of the residuals, if we take the square root of the MSE we find the standard deviation of the residuals, which is the standard error of estimate.
  • https://stats.libretexts.org/Workbench/Introduction_to_Statistical_Methods_(Yuba_College)/04%3A_Correlation_and_Regression/4.04%3A_Residuals
    The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterp...The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterplot vertically as a yellow double-sided arrow to visually show the size of the residual. The mean square error is the variance of the residuals, if we take the square root of the MSE we find the standard deviation of the residuals, which is the standard error of estimate.
  • https://stats.libretexts.org/Courses/Cerritos_College/Introduction_to_Statistics_with_R/13%3A_Introduction_to_Linear_Regression/13.02%3A_Line_Fitting_Residuals_and_Correlation
    In this section, we examine criteria for identifying a linear model and introduce a new statistic, correlation.
  • https://stats.libretexts.org/Courses/Cerritos_College/Introduction_to_Statistics_with_R/21%3A_Math_Review_for_Introductory_Statistics/21.06%3A_Graphing_Points_and_Lines_in_Two_Dimensions/21.6.01%3A_Finding_Residuals
    In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observe...In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observed value of y and  y based on the equation of the regression line.
  • https://stats.libretexts.org/Courses/Fullerton_College/Math_121%3A__Support_for_Introductory_Probability_and_Statistics/08%3A_Graphing_Points_and_Lines_in_Two_Dimensions/8.07%3A_Finding_Residuals
    In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observe...In the linear regression part of statistics we are often asked to find the residuals. Given a data point and the regression line, the residual is defined by the vertical difference between the observed value of y and  y based on the equation of the regression line.
  • https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Mostly_Harmless_Statistics_(Webb)/12%3A_Correlation_and_Regression/12.02%3A_Simple_Linear_Regression/12.2.02%3A_Residuals
    The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterp...The numeric value of the residual is found by subtracting the predicted value of \(y\) from the actual value of \(y\): \(y - \hat{y}\). The residual for the point \((15, 80)\) is drawn on the scatterplot vertically as a yellow double-sided arrow to visually show the size of the residual. The mean square error is the variance of the residuals, if we take the square root of the MSE we find the standard deviation of the residuals, which is the standard error of estimate.

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