6- (15%) Assume that X=The final grade of a student in Stochastic Modeling class and Y=The...
6- (15%) Assume that X=The final grade of a student in Stochastic Modeling class and Y=The final grade of a student in Structural Analysis class The joint probability of the grades earned by a student is P(X,Y) which is as follows. Stochastic Modeling Grades 90 75 Structural Analysis Grades 95 0.2 0.3 80 0.4 0.1 How the grades of Stochastic and Structural Analysis classes are related to each other? (Positive, Negative or no relationship?) *Hint: No need for the final...
6- (15%) Assume that X=The final grade of a student in Stochastic Modeling class and Y=The final grade of a student in Structural Analysis class The joint probability of the grades earned by a student is P(X,Y) which is as follows. Stochastic Modeling Grades Structural Analysis Grades 95 0.2 0.3 90 75 80 0.4 0.1 How the grades of Stochastic and Structural Analysis classes are related to each other? (Positive. Negative or no relationship?) *Hint: No need for the final...
6- (15%) Assume that X=The final grade of a student in Stochastic Modeling class and Y=The final grade of a student in Structural Analysis class The joint probability of the grades earned by a student is P(X,Y) which is as follows. Stochastic Modeling Grades Structural Analysis Grades 95 0.2 0.3 90 75 80 0.4 0.1 How the grades of Stochastic and Structural Analysis classes are related to each other? (Positive, Negative or no relationship?) *Hint: No need for the final...
6- (15%) Assume that X= The final grade of a student in Stochastic Modeling class and Y= The final grade of a student in Structural Analysis class. The joint probability of the grades earned by a student is P(X,Y) which is as follows. Structural Analysis Grades Stochastic Modeling Grades: 95, 80, 90, 0.2, 0.4, 75, 0.3, 0.1 How the grades of Stochastic and Structural Analysis classes are related to each other? (Positive, Negative or no relationship?) *Hint: No need for...
(1 point) A study was conducted to determine whether the final grade of a student in an introductory psychology course is linearly related to his or her performance on the verbal ability test administered before college entrance. The verbal scores and final grades for all 10 students in the class are shown in the table below. Student Verbal Score x Final Grade y 49 77 51 67 69 81 61 61 47 62 73 41 59 90 65 82 26...
1 76 (6 points) A study was conducted to determine whether the final grade of a student in an introductory psychology course is linearly related to his or her performance on the verbal ability test administered before college entrance. The verbal scores and final grades for all 10 students in the class are shown in the table below. Student Verbal Score x Final Grade y 34 78 2 56 3 76 68 4 34 76 5 33 60 6 49...
46 2 (6 points) A study was conducted to determine whether the final grade of a student in an introductory psychology course is linearly related to his or her performance on the verbal ability test administered before college entrance. The verbal scores and final grades for all 10 students in the class are shown in the table below. Student Verbal Score x Final Grade y 1 86 42 77 3 41 87 4 39 98 5 79 75 6 41...
The regression equation, y ˆ = 93.11 - 7.196x, expresses statistical dependence of the final grade in statistics (y) on the number of classes missed by students (x) in a sample of 75 statistics students. If the coefficient of determination is r^2 = 0.5921, how much of the variation of the final grades in statistics can be explained by the variation of the numbers of classes missed by students?
The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below. No. of absences, x 0 1 2 3 4 5 6 7 8 9 Final grade, y 88.1 85.1 82.1 79.6 76.5 72.0 62.3 66.7 63.7 60.7 (a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as...
Run a regression analysis on the following data set, where y is the final grade in a math class and x is the average number of hours the student spent working on math each week. hours/week x Grade y x y 4 40.6 6 62.4 7 68.8 8 70.2 10 76 11 82.4 13 77.2 14 79.6 15 96 19 100 State the regression equation y = m ⋅ x + b , with constants accurate to two decimal places....