Question

Run a regression analysis on the following data set, where is the final grade in a math class and is the average number of hours the student spent working on math each week.

hours/week
x Grade
y
5 60
5 49
5 50
6 59.4
6 58.4
11 73.4
13 88.2
14 73.6
15 83
19 90.6


State the regression equation , with constants accurate to two decimal places.


What is the predicted value for the final grade when a student spends an average of 12 hours each week on math?
Grade =
Round to 1 decimal place.

Answer 1

To perform a regression analysis on hours spent studying and grades, input the data into statistical software to find the regression equation and predict the grade for a student studying 12 hours a week.

Step-by-step explanation:

To run a regression analysis on the provided data set comprising the number of hours per week a student spends studying (x) and their respective final grade (y), we use the method of least squares to find the best-fitting line. The variables in the data set are as follows:

• Hours/Week (x)
• Grade (y)

Using statistical software or a calculator, we input the data points and calculate the linear regression equation, which typically has the form:

y = a + bx

Where a is the y-intercept and b is the slope of the line. After calculating the values of a and b, we can then find the predicted grade for a student who studies an average of 12 hours each week by substituting 12 for x in the regression equation and rounding the result to one decimal place.

It's important to note that while this method provides an estimate based on the data, actual grades can vary due to other factors not accounted for in the regression model.