Hi Anonymous Pistol,
In order to answer this question you actually do not have to compute anything - it follows from the definition of a confidence interval.
The 95% interval implies that you are 95% confident that the true proportion lies within the boundaries of your interval, so in this case that it is between 0.6 and 0.7. Also in general, a 95 % confidence interval corresponds to a two-tailed hypothesis test with an alpha level of 5% ( 100 - 95%) .
The hypothesized proportion is 0.63, which is right within that confidence interval. This would mean that you would fail to reject that hypothesis at the 5% alpha level, hence the corresponding p-value (which is the probability of observing such a test statistic or an even more extreme one, if the null hypothesis were true) needs to be larger than 5%.
So just as a general take-away: if the hypothesized value is within the boundaries of the interval, the corresponding p-value will be larger than (100- stated confidence level). If it is not within the confidence interval, then the p-value will be smaller than 100% - CL.
Hope that helps!
We wish you success!
Your Success Formula Team - Lena