Find the equation of the regression line for the given data. then construct a scatter plot of the data and draw the regression line. (the pair of variables have a significant correlation.) then use the regression equation to predict the value of y for each of the given x-values, if meaningful. the number of hours 6 students spent for a test and their scores on that test are shown below. x 0 2 3 3 5 6 y 39 46 52 45 62 70

The given data is
x:    0    2     3    3    5    6
y:  39  46  52  45  62  70

Use the graphing calculator, Microsoft Excel, or similar software to find the least squares linear regression fit to the data.
The fitted data is shown in the graph below.

The regression line is
y = 35.876 + 5.197x

The correlation coefficient of R² indicates that the curve fit is good and reasonably acceptable.

The given data versus predicted values are shown in the following table.
The outlier at x = 3 is omitted.

x     y (data)  y (predicted)
---   -----------  ------------------
0        39       35.876
2        46       47.470
3         52      53.267
5         62      64.861 
6         70      70.658

The percent increase is 25%