I'm of course very sorry to hear this. Here's the good news: it seems like the questions that were missed the most are number system/conversion/arithmetic questions. This is good news because a) at least you know now and b) these kinds of questions are very easy to drill-and-skill on later on for test prep.
The focus of the unit, of course, does not require you to memorize some of these things or give a ton of practice going back and forth and I would also surmise it's not a huge point of emphasis for the real exam.
The question about heuristics is tough here since it's only been briefly addressed.
And the question about "lossy v. lossless" is quite tricky because it asks you to apply those terms outside the context you likely learned them in (compression). That question merits a longer teacher explanation which I have now added to the question (it will go live in next ~24 hours). But I've copied below.
HAVE FAITH AND STICK WITH IT. You will not believe how much your students grow and learn and will think these questions are easy later in the year. Remember to remind them that these questions are AP-style questions and they're seeing them early. It's a measuring stick, not a judgement.
------ Explanation of Lossy v. Lossless transformation question ----
The answer is "lossless" transformation because there is a computational process you can perform on the transformed data to recover the original (namely, subtract 20). `The question is carefully formulated to ensure that this is true.
This question is tricky for a few reasons:
it is carefully formulated with starting assumptions and values that ensure the transformation is lossless. If you applied this transformation willy-nilly it might be lossless (see below).
it applies the terms lossy and lossless outside the context they are usually presented (compression)
because of the fact that the data is being transformed and overwritten, you might be tricked into thinking that the data is "lost". But the transformation itself is lossless because you can apply a computational process to the transformed data to recover every bit of the original information.
It would be "lossy" if the transformation did something that would not let you recover every bit.
For example: If the question stated that you add 200 to each RGB channel, it might be lossy, because if, say, one of the RGB values was (75, 57, 99), adding 200 to each would max out the values at 255 - since an RGB value cannot be greater than 255 - the resulting transformation would be the RGB value (255, 255, 255).
Reversing the process, subtracting 200 from each of the transformed values does not restore the original. Since there is no process or computation you can perform on the transformed data to recover the original, it is "lossy".