For visual evaluation, the histogram is far more useful than a
cumulative frequency graph.
A more discriminating qualitative approach would be to do a normal
probability plot. Mike Middleton has a downloadable paper on this at
http://www.usfca.edu/~middleton/data.htm
Excel is not a statistics program (though it can be used to do
statistics) and has no built-in normality tests.
The usual quantitative tests, such as Shapiro-Wilk would require that
you insert tabled values
http://www.itl.nist.gov/div898/handbook/prc/section2/prc213.htm
or use a commercial Add-In such as
http://www.analyse-it.com/shapiro-wilk-normality-test_y.htm
You could do a rough and ready chi-square test, by dividing the real
line into a n intervals, each having an expected value under normality
of at least 5 observations with your sample size. Then sum
(Observed-Expected)^2/Expected and compare to CHIINV(alpha,n-1) where
alpha is suitably small (say 0.05)
More generally, you could do a Kolmogorov-Smirnov test, but again you
would have to program it yourself.
If you are wanting to do heavy duty statistical analysis on a budget and
no longer have access to Minitab and SPSS, have a look at R. It is an
open source statistical package (using the S language) that is freely
available
http://www.r-project.org
Jerry