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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION

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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
A professor investigated some of the factors that affect an individual student's final grade in his course.He proposed the multiple regression model Y = β0 + β1X1 + β2X2 + β3X3 + ε ,where Y is the final mark (out of 100),X1 is the number of lectures skipped,X2 is the number of late assignments,and X3 is the mid-term test mark (out of 100).The professor recorded the data for 50 randomly selected students.The computer output is shown below.
The regression equation is THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A professor investigated some of the factors that affect an individual student's final grade in his course.He proposed the multiple regression model Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + ε ,where Y is the final mark (out of 100),X<sub>1</sub> is the number of lectures skipped,X<sub>2</sub> is the number of late assignments,and X<sub>3</sub> is the mid-term test mark (out of 100).The professor recorded the data for 50 randomly selected students.The computer output is shown below. The regression equation is = 41.6 - 3.18x<sub>1</sub> - 1.17x<sub>2</sub> + 0.63x<sub>3</sub>. S = 13.74 R-Sq = 30.0% ANALYSIS OF VARIANCE -Does the data provide enough evidence to conclude that,at the 5% significance level,the final mark and the number of skipped lectures are linearly related?
= 41.6 - 3.18x1 - 1.17x2 + 0.63x3.
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A professor investigated some of the factors that affect an individual student's final grade in his course.He proposed the multiple regression model Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + ε ,where Y is the final mark (out of 100),X<sub>1</sub> is the number of lectures skipped,X<sub>2</sub> is the number of late assignments,and X<sub>3</sub> is the mid-term test mark (out of 100).The professor recorded the data for 50 randomly selected students.The computer output is shown below. The regression equation is = 41.6 - 3.18x<sub>1</sub> - 1.17x<sub>2</sub> + 0.63x<sub>3</sub>. S = 13.74 R-Sq = 30.0% ANALYSIS OF VARIANCE -Does the data provide enough evidence to conclude that,at the 5% significance level,the final mark and the number of skipped lectures are linearly related?
S = 13.74 R-Sq = 30.0%
ANALYSIS OF VARIANCE
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A professor investigated some of the factors that affect an individual student's final grade in his course.He proposed the multiple regression model Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + ε ,where Y is the final mark (out of 100),X<sub>1</sub> is the number of lectures skipped,X<sub>2</sub> is the number of late assignments,and X<sub>3</sub> is the mid-term test mark (out of 100).The professor recorded the data for 50 randomly selected students.The computer output is shown below. The regression equation is = 41.6 - 3.18x<sub>1</sub> - 1.17x<sub>2</sub> + 0.63x<sub>3</sub>. S = 13.74 R-Sq = 30.0% ANALYSIS OF VARIANCE -Does the data provide enough evidence to conclude that,at the 5% significance level,the final mark and the number of skipped lectures are linearly related?
-Does the data provide enough evidence to conclude that,at the 5% significance level,the final mark and the number of skipped lectures are linearly related?

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H0 : β1 = 0 against H1 : β1 ≠ 0
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