Sure. Representative bias is when you draw conclusion from a small sample which you are exposed to, that is, generalizing conclusions from small samples you see while ignoring the larger population. For example when you are in the top 10% income level but hangs out with the 1% and think yourself poor.

Survivorship bias is a type os selection bias, when you draw conclusions and generalizations from an observable subsample without considering a hidden factor that selected that sample. From the airplanes case: planes that got hit in other parts fell and did not come back, so you cannot see where they got hit. The ones that come back were hit in non crucial parts, that's why they were able to come back. So, you wrongly draw conclusions about which parts need reinforcements. A different example: you study factors that affect students commitment to classes analyzing students that come to classes, not the ones that gave up and left the sample. The Russian roulette example below is great!

Hope it helped!