A group of university students is exploring the connection between study hours and academic performance. They gather data on weekly study hours and corresponding GPAs. The study hours range from 5 to 40 per week, and GPAs vary between 2.0 and 4.0. The students aim to find a mathematical relationship that can predict GPA based on study hours. They calculate summary statistics such as the mean and standard deviation for study hours and GPA. The data showed that the average study hours might be 20, with a standard deviation of 10, and the average GPA might be 3.0, with a standard deviation of 0.5. They also calculate the correlation between study hours and GPA to measure the strength of the linear relationship to be 0.65. This analysis could provide valuable insights for students looking to optimize their study habits and improve their academic performance. However, it’s important to remember that correlation does not imply causation, and other factors may also influence a student’s GPA. Calculate the y-intercept of the regression line.
A group of university students is exploring the connection between study hours and academic performance. They gather data on weekly study hours and corresponding GPAs. The study hours
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