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In a Simple Regression with an Intercept and a Single

Question 42

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In a simple regression with an intercept and a single explanatory variable,the variation in Y In a simple regression with an intercept and a single explanatory variable,the variation in Y can be decomposed into the explained sums of squares and the sum of squared residuals (see,for example,equation (4.35)in the textbook). Consider any regression line,positively or negatively sloped in {X,Y} space.Draw a horizontal line where,hypothetically,you consider the sample mean of Y to be.Next add a single actual observation of Y. In this graph,indicate where you find the following distances: the (i)residual (ii)actual minus the mean of Y (iii)fitted value minus the mean of Y can be decomposed into the explained sums of squares In a simple regression with an intercept and a single explanatory variable,the variation in Y can be decomposed into the explained sums of squares and the sum of squared residuals (see,for example,equation (4.35)in the textbook). Consider any regression line,positively or negatively sloped in {X,Y} space.Draw a horizontal line where,hypothetically,you consider the sample mean of Y to be.Next add a single actual observation of Y. In this graph,indicate where you find the following distances: the (i)residual (ii)actual minus the mean of Y (iii)fitted value minus the mean of Y and the sum of squared residuals In a simple regression with an intercept and a single explanatory variable,the variation in Y can be decomposed into the explained sums of squares and the sum of squared residuals (see,for example,equation (4.35)in the textbook). Consider any regression line,positively or negatively sloped in {X,Y} space.Draw a horizontal line where,hypothetically,you consider the sample mean of Y to be.Next add a single actual observation of Y. In this graph,indicate where you find the following distances: the (i)residual (ii)actual minus the mean of Y (iii)fitted value minus the mean of Y (see,for example,equation (4.35)in the textbook).
Consider any regression line,positively or negatively sloped in {X,Y} space.Draw a horizontal line where,hypothetically,you consider the sample mean of Y In a simple regression with an intercept and a single explanatory variable,the variation in Y can be decomposed into the explained sums of squares and the sum of squared residuals (see,for example,equation (4.35)in the textbook). Consider any regression line,positively or negatively sloped in {X,Y} space.Draw a horizontal line where,hypothetically,you consider the sample mean of Y to be.Next add a single actual observation of Y. In this graph,indicate where you find the following distances: the (i)residual (ii)actual minus the mean of Y (iii)fitted value minus the mean of Y to be.Next add a single actual observation of Y.
In this graph,indicate where you find the following distances: the
(i)residual
(ii)actual minus the mean of Y
(iii)fitted value minus the mean of Y

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