Ideally, you want to find a slope of zero. If the slope is significantly different from zero, you can conclude that there is a significant relationship between the size of the part or variable measured as a standard and the ability to measure. The null hypothesis is that the slope is 0. Your p-value is a good deal higher than 0.05 so you fail to reject the null hypothesis that the slope is 0.
The test for the intercept is useful only if the test on the slope fails to reject the hypothesis of slope = 0. You failed to reject the hypothesis so you are interested in this test. The test for the intercept is a test of bias. Again, your p-value is a good deal higher than 0.05 so you also fail to reject the null hypothesis that the intercept (bias) is 0.
gucafg0: Just to reinforce tonya.mauldin0's phraseology regarding 'failure to reject the null hypothesis', you should NEVER 'accept' a null hypothesis using any inferential tests. All you can do with any inferential test is reject or fail to reject the null hypothesis. Failure to reject is not synonymous with acceptance...morally or statistically.