Final answer:
Without an exact regression equation, it is not possible to accurately predict the final exam grade of a student who studied for 6 hours based on the information provided.
Step-by-step explanation:
To predict the exam grade of a student who studied for 6 hours, we need to determine if there is a linear relationship between the number of hours spent studying and final exam grades. We would typically use a regression equation for this purpose. However, the information provided does not include a specific regression equation that correlates study hours with exam scores. We can use the information provided to make informed guesses, though these would not replace an actual prediction based on a given regression equation.
From Example 2.22, we understand that the 30th percentile of students studies for seven or fewer hours per week. This indicates that a student who studies for 6 hours is just below the 30th percentile in terms of study hours. Meanwhile, 38. indicates that college students, on average, study less than 20 hours per week. Without specific data linking study hours to grades, we can say that a student studying for 6 hours is likely studying less than average.
Similarly, information in 68. informs us about the probability of studying at least 15 hours and making the honor roll, but this does not directly provide us with the information needed for students studying 6 hours. Lastly, from 173.51 + 4.83(73), we understand that there is a method of predicting final exam scores from third exam scores using a linear equation, but this does not directly relate to study hours.
Therefore, without an exact regression equation that correlates the number of study hours to final exam grades, we cannot accurately predict the final exam score of a student who studied for 6 hours. An empirical examination of the data would be required to establish such a relationship.