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In a Simple Regression with an Intercept and a Single

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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


Definitions:

Elimination

The process of removing something or someone from consideration, or the body's process of expelling waste.

Hepatitis

Inflammation of the liver, often caused by viral infections, toxins, medications, or autoimmune disease.

Hepatoma

A malignant tumor of the liver, also known as hepatocellular carcinoma, which is common in individuals with chronic liver diseases.

Nephritis

Inflammation of the kidneys, which can alter their function and is classified by the location such as glomerulonephritis or interstitial nephritis.

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