Hi Salma,
Given that we don't know a population standard deviation, we have to use t rather than z. Test statistic is:
t=x-bar-mu/SE
Breaking this down:
x-bar=sample mean
mu=popularion mean
SE=standard error, which has its own formula
SE=s/sqrt (n)
s=sample standard deviation
n=sample size
Now, for our sample:
s=14.1
n=8
SE=14.1/sqrt(8)
SE=4.986
Now, returning to the original formula:
t=(x-bar-mu)/SE
x-bar=65.5
mu=55.5
SE=4.986
t=(65.5-55.5)/4.986
t=2.005
Now, let's talk about degrees of freedom (df)
df=n-1
n=sample size=8
df=8-1
df=7
So, go to the t-table, look at the row for 7 degrees of freedom, and find the test statistic 2.005. It falls between 1.895 and 2.365, which corresponds, for two-sided tests, to p-values of 0.10 and 0.05 respectively. Therefore:
0.0500 < p < 0.1000
We cannot get any closer estimate of p-value without using statistical software. I hope this helps.