.01 means 1%, this is lower (and thus more significant) than 5%. So if you have determined that your critical significance level is 5% or lower, than a result of .01 would be considered significant.

Angela - 

You need a type II error analysis, or other sensitivity analysis.  A p-value does not stand alone as a useful statistic for any test.

See the following:

Press release for the American Statistical Association:

http://www.amstat.org/newsroom/pressreleases/P-ValueStatement.pdf

 https://www.researchgate.net/publication/262971440_Practical_Interpretation_of_Hypothesis_Tests_-_letter_to_the_editor_-_TAS

To validate regression, you could leave out some of your y data and see how well you would have predicted for it using the other data.  

You might also consider the estimated variance of the prediction error, the square root of which is STDI in SAS PROC REG, for example.  

Best wishes - Jim 

Article Practical Interpretation of Hypothesis Tests - letter to the...

Yes, James is correct concerning p-value, however, 0.01 suggests that there is possible nonlinearity in the data. A graph of the data is bound to show that. Therefore, if the graph is not linear, the evidence than you have a possible disease in your estimated parameter.