A teacher wants to predict a students grade average for her class cased on the number of hours that the student missed class.. She computes the regression equation to be y = -2.5x + 105 a. What is the students predicted average if they miss 6 hours of class b. The correlation coefficient for the problem is? Make an estimate, then explain what this means in terms of the situation c. What does the slope mean in terms of the situation d. What does the y intercept mean in terms of the situation
A teacher wants to predict a students grade average for her class cased on the number...
A teacher wants to predict a students grade average for her class cased on the number of hours that the student missed class.. She computes the regression equation to be y = - 2.5x + 105 a. What is the students predicted average if they miss 6 hours of class? b. The correlation coefficient for the problem is? Make an estimate, then explain what this means in terms of the situation? c. What does the slope mean in terms of the...
8. A teacher wants to predict a students grade average for her class cased on the number of hours that the student missed class.. She computes the regression equation to be y -- 2.5x + 105 a. What is the students predicted average if they miss 6 hours of class? (5) b. The correlation coefficient for the problem is? Make an estimate, then explain what this means in terms of the situation? (5) c. What does the slope mean in...
Suppose a teacher recorded the attendance of her students in a recent statistics class because she wanted to investigate the linear relationship between the number of classes they missed and their final grades. The accompanying table shows these data for a random sample of nine students. Complete parts a through c. Click the icon to view the table showing missed classes and final grade. a. Using a =0.02, test the significance of the regression slope. The hypotheses for this test...
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...
Suppose a teacher recorded the attendance of her students in a
recent statistics class because she wanted to investigate the
linear relationship between the number of classes they missed and
their final grades. The accompanying table shows these data for a
random sample of nine students
Classes Missed Final Grade
4 73
6 81
1 92
4 72
0 94
2 86
0 89
5 87
2 96
Suppose a teacher recorded the attendance of her students in a recent...
The table below gives the number of absences and the overall grade in the class for five randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1xy^=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...
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 Grade х у 4 41.6 4 54.6 8 68.2 8 73.2 8 66.2 11 63.4 11 70.4 11 80.4 13 71.2 16 85.4 State the regression equation y = mx + b, with constants accurate to two decimal places. What is the predicted value...
Suppose a teacher recorded the attendance of her students in a recent statistics class because she wanted to investigate the linear relationship between the number of classes they missed and their final grades. The accompanying table shows these data for a random sample of nine students. Complete parts a through c. Click the icon to view the table showing missed classes and final grade. a. Calculate the correlation coefficient for this sample. The correlation coefficient is I. (Type an integer...
Twenty students took a test. The average grade was 86 with a standard deviation of 9. Data was collected for x: minutes studies and y: score on test The correlation coefficient was r = .43 The regression line was ŷ = -12 + .75x What score do you predict for someone that studied 120 minutes ___________ Data was collected for x: grade point and y: score on test The correlation coefficient was r = .76 The regression line was ŷ...
Grade point average. The director of admissions of a small college seleeted 120 students at random from the new freshman class in a study to determine whether a student's grade point average (GPA) at the end of the freshman year (Y) can be predicted from the ACT test score (X) The results of the study follow. Assume that first-order regression model (1.1) is appropriate. 2 118 119 120 i: Xi: 21 Yi: 14 28 28 16 28 3.897 3.885 3.778.....