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Student Year in College Course Work Hours per Class Freshman (1) 2 Sophomore (2) 3 Junior (3) 4 4 Senior (4) A scatterplot of the sample data follows [blue points (circle symbols)]. The line Y = 8 - X is also HOURS 10 O Sum of Distances 8 0 (x-bar, y-bar)) х 5 YEAR Clear All 2. 2. The difference between Y and Ỹ for a particular sample point (observation) is called a residual. Suppose you use the least squares method to find the least squares regression line for the four sample points on the graph. On the basis of your work so far, even before you fit the line, you know that the sum of the residuals is . In addition, being as specific as you can be, you know that the sum of the squared residuals is The slope of the least squares regression line is b = . The intercept of the least squares regression line is a = On the following scatterplot of the blue sample points (circle symbols), use the orange line (square symbols) to plot the least squares regression line. Place the first orange square at the left edge of the graph (the intercept) and the second orange square at the value of Ý at the right edge of the graph. HOURS 10 Regression Line 3 1 3 4. YEAR Clear All

Student Year in College Course Work Hours per Class Freshman (1) 2 Sophomore (2) 3 Junior (3) 4 4 Senior (4) A scatterplot of the sample data follows [blue points (circle symbols)]. The line Y = 8 - X is also HOURS 10 O Sum of Distances 8 0 (x-bar, y-bar)) х 5 YEAR Clear All 2. 2. The difference between Y and Ỹ for a particular sample point (observation) is called a residual. Suppose you use the least squares method to find the least squares regression line for the four sample points on the graph. On the basis of your work so far, even before you fit the line, you know that the sum of the residuals is . In addition, being as specific as you can be, you know that the sum of the squared residuals is The slope of the least squares regression line is b = . The intercept of the least squares regression line is a = On the following scatterplot of the blue sample points (circle symbols), use the orange line (square symbols) to plot the least squares regression line. Place the first orange square at the left edge of the graph (the intercept) and the second orange square at the value of Ý at the right edge of the graph. HOURS 10 Regression Line 3 1 3 4. YEAR Clear All

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter2: Equations And Inequalities
Section2.1: Equations
Problem 78E
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Student Year in College Course Work Hours per Class Freshman (1) 2 Sophomore (2) 3 Junior (3) 4 4 Senior (4) A scatterplot of the sample data follows [blue points (circle symbols)]. The line Y = 8 - X is also HOURS 10 O Sum of Distances 8 0 (x-bar, y-bar)) х 5 YEAR Clear All 2. 2.
Transcribed Image Text:Student Year in College Course Work Hours per Class Freshman (1) 2 Sophomore (2) 3 Junior (3) 4 4 Senior (4) A scatterplot of the sample data follows [blue points (circle symbols)]. The line Y = 8 - X is also HOURS 10 O Sum of Distances 8 0 (x-bar, y-bar)) х 5 YEAR Clear All 2. 2.
The difference between Y and Ỹ for a particular sample point (observation) is called a residual. Suppose you use the least squares method to find the least squares regression line for the four sample points on the graph. On the basis of your work so far, even before you fit the line, you know that the sum of the residuals is . In addition, being as specific as you can be, you know that the sum of the squared residuals is The slope of the least squares regression line is b = . The intercept of the least squares regression line is a = On the following scatterplot of the blue sample points (circle symbols), use the orange line (square symbols) to plot the least squares regression line. Place the first orange square at the left edge of the graph (the intercept) and the second orange square at the value of Ý at the right edge of the graph. HOURS 10 Regression Line 3 1 3 4. YEAR Clear All
Transcribed Image Text:The difference between Y and Ỹ for a particular sample point (observation) is called a residual. Suppose you use the least squares method to find the least squares regression line for the four sample points on the graph. On the basis of your work so far, even before you fit the line, you know that the sum of the residuals is . In addition, being as specific as you can be, you know that the sum of the squared residuals is The slope of the least squares regression line is b = . The intercept of the least squares regression line is a = On the following scatterplot of the blue sample points (circle symbols), use the orange line (square symbols) to plot the least squares regression line. Place the first orange square at the left edge of the graph (the intercept) and the second orange square at the value of Ý at the right edge of the graph. HOURS 10 Regression Line 3 1 3 4. YEAR Clear All
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