Taking a test i don’t know anything about please help
In an Economics course, the correlation between the students' total score prior to the final exam and
their final exam score is r = 0.60. The pre-exam totals for all students in the course have mean 280
points and standard deviation 30 points. The final exam scores have mean 75 points and standard
deviation 8 points.
4. Find the equation of the least-squares regression line for predicting a final exam score from a
student's pre-exam total.
5.
Interpret the slope in context.
6.
Interpret the y-intercept in context.
7.
Calculate the fraction of variability, R?.
8.
Interpret R? in context.

We are given that [tex]\overline y=75[/tex], [tex]s_y=8[/tex], [tex]\overline x=280[/tex], [tex]s_x=30[/tex], and [tex]r=0.60[/tex], therefore our slope, [tex]b[/tex], is:

[tex]b=\frac{r*s_y}{s_x}[/tex]

[tex]b=\frac{(0.60)(8)}{30}[/tex]

[tex]b=0.16[/tex]

Therefore, the slope of the regression line is 0.16, which can be used along with the values of [tex]\overline y[/tex] and [tex]\overline x[/tex] to find the constant [tex]a[/tex]:

[tex]a=\overline y-b \overline x[/tex]

[tex]a=75-(0.16)(280)[/tex]

[tex]a=30.2[/tex]

This means our final regression line is [tex]\hat y = 30.2 + 0.16x[/tex]

Problem 5:

The slope, [tex]b=0.16[/tex], means that for every 1 point earned for a student's pre-exam total, their final exam score will increase by 0.16 points for each point they earned on the pre-exam.

Problem 6:

The y-intercept (or constant), [tex]a=30.2[/tex], means that if a student's pre-exam total were 0, then they would expect to get a 30.2 on the final exam.

Problem 7:

[tex]R^{2}=(0.60)^{2}=0.36=36\%[/tex]

Problem 8:

The fraction of variability (aka. coefficient of determination), [tex]R^2[/tex], means that a certain proportion (or percentage) of the variance in the response variable can be explained by the explanatory variable. In context, this means that 36% of the variance in final exam scores can be explained by the pre-exam scores.