Precision and Quantifier

The past two weeks of class we covered some basic understanding of the logical thinking we need in order to succeed at Computer Science.

First off, we started with precision- just how precise do we need to be for a computer to understand us? What's a good balance? How do we "translate" human language into one computers can comprehend? We learned to run some basic code in Python and how to simplify code. I feel that even though simplified code might be saving space and more efficient, they are harder to understand by someone looking at the code for the first time. To debug a code, having a long string of logical argument may slow down progress. I find that reading code such as "return any([x not in S2 for x in S1])" takes more energy and requires more thinking to understand, as opposed to a "if-then" statement. To work on this, I will review the notes often and practice more questions.

The second topic we covered in class was Quantifiers. While the real world application of quantifiers is broad and I've come into contact with it quite a lot, I've never thought about it in such detail as we did in class. We learned how to prove/disprove statements, whether it be universal quantifiers or existential quantifiers. In the second week of classes, we evaluated the claims the quantifiers made- with python programs. This required logical thinking and determining the outcome.

Lastly, we learned about sentences and statements, as well as implications. We should take care the distinction between sentences and statements, as we need to identify them. For implications, cause and effect is a main concern. I had some troubles differentiating between some questions the "P" and "Q". This will require more work and more practice.