Question

1. The following data represents the number of days absent and the final grade for a sample of college students in a general education course at a large state university.

No. of absences 0 1 2 3 4 5 6 7 8 9

Final Grade 89.2 86.4 83.5 81.1 78.2 73.9 64.3 71.8 65.5 66.2

a) Which variable is the explanatory variable?

b) Draw a scatter plot and describe your scatter plot (Direction, Strength, Form).

c) Compute the correlation coefficient.

d) Does a linear relation exist between the number of absences and the final grade? Justify your answer.

e) Write out the least-squares regression line equation.

f) Compute and draw the residual (on your scatter plot) for a student who misses 5 class meetings.

g) Explain the slope in context.

h) Is the y-intercept meaningful in this situation? Explain.

i) Compute and interpret the coefficient of determination.

j) Construct a residual plot to verify the requirements of the least-squares regression model.

Answer 1

cal No. of absences the explanatory variable ch its strung negative conection R²= 0.8976 R250.8976 R = 10.8976 = 0.9474 R = -0.9474 (d) yes because we have strong negative Corelation and linear also its Final grade = 88.733 - 2.8273 (x) x=5 Final grade = 88.733-218273(5) Final grade = 7460 now Residual Actual - predicte of 78.2- 74,60 36 Residuat 3.6 When No. of absences absences increase then final decrease by - 28273 (g) grade ch) No. becaure then is no absence Then Final grade would be 88.73 This is not meaningful