The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x , for using the number of absences to predict a student's overall grade in the class. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Number of Absences Grade 1 3.7 2 3.3 3 3.1 4 2.9 6 2.4 7 2.2 8 1.9 According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable yˆ is given by? a. b0 b. b1 c. x d. y
The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x , for using the number of absences to predict a student's overall grade in the class. Keep in mind, the
Number of Absences Grade
1 3.7
2 3.3
3 3.1
4 2.9
6 2.4
7 2.2
8 1.9
According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable yˆ is given by?
a. b0
b. b1
c. x
d. y
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