Just to be clear, the expected result from a hypothesis test is whether the researcher (you) is rejecting or failing to reject the null hypothesis. The heuristic adopted to go for one or the other is called the decision rule; basically, the rule used to either reject the null hypothesis or not.
The most common decision rule is to fix a limit to the significance level in advance. This limit can be seen as the greater probability of committing a type I error you're willing to risk; that is, the greater chance to reject the null hypothesis while it was actually right. Common numbers are 5% and 1% (these are usually arbitrary).
With your number at hand, you can check whether the p-value ...
