Answer:
a)
b)
For our case we have this:
n=10
And the variation coeffcient would be 
And we can conclude that the linear model explains 57.9 % of the variation.
Explanation:
a. Plot the data and the model.
Data given:
X: 42 5 25 10 4 15 20 12 14 22
Y: 1.5 4 2.1 2.6 4.8 2 2.5 3.3 1.9 2
For this case we need to calculate the slope with the following formula:
Where:
So we can find the sums like this:
With these we can find the sums:
And the slope would be:
Nowe we can find the means for x and y like this:
And we can find the intercept using this:
So the line would be given by:
The plot on this case is on the figure attached.
b. How good is a fit?
For this case we can calculate the correlation coefficient with the following formula:
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
And in order to calculate the correlation coefficient we can use this formula:
For our case we have this:
n=10
And the variation coefficient would be 
And we can conclude that the linear model explains 57.9 % of the variation.