The t-test is a good test for these data. Your graphs indicate that the mean height of DC is greater than the mean height of DP, but in statistics "greater than" is different than "significantly greater than." As Larry mentions, you'd need more data to be able to claim that the height of DC is *significantly* greater than the height of DP.

Larry also notes that the variances of each group might vary. PROC TTEST can account for that as well. Look at the "Satterthwaite" statistic in the TTEST output, instead of the "Pooled" statistic. In either case, the differences between the DC and DP means are not significant at a 95% level. (Sorry!)

What I think is interesting is how much the heights degraded in the third trial. You can use the Interaction Plot in PROC GLM to examine the effect of the Trial parameter:

ods graphics on;
proc glm data=results;
class Brand Trial;
model Height = Brand Trial;
run;

The Trial parameter is a significant factor. I think the main result of your daughter's experiment is "the reaction between soda and mentos depends (strongly) on the freshness of the soda."

This statement assumes that the temperature was the same in all trials; if not, the Trial parameter might actually be a proxy for "cooler temperature." This suggests another science fair product: compare room temperature soda to refrigerated soda.