This is how you do analysis. You look at the data and see what additional insights you can draw, you evaluate your original assumption and update it from the new data.

For example, we have what is likely an outlier group here (we actually probably have 2, 1 young 1 old). And you look at what the data looks like without the outlier. Does this provide more insight? Is there something unusual about the group you excluded that makes it necessary or not necessary to include. What do these separated data tell you now? Was this group just padding "no's"? Were they even relevant to ask or should we assume they never were going to be "yes's".

Its one step of many to the next iteration of analysis and research.

Additionally, its pretty common to bucket out 18-64 in a lot of research, especially things like media (media often uses 18-54, 55+, or 65+). Even moreso, we have a pretty good understanding of the 65+ group in media much more than younger groups in how they consume and spend on media (there's lots to say here but its getting deep technical).

In otherwords, there isn't juicing, what you want to do is see what the hell is happening, and adjusting the data to look at it from different angles is one step and seeing where things fit.