MATH 4110

Other reviews have already summarized the logistics of the course, so I'm just here to add that the structure was truly awful in my opinion. Since the homeworks aren't turned in and the textbook doesn't have solutions, there's no way to actually invest time practicing and studying the material fully because you don't get anything graded back until after the quiz. Notation in other textbooks is radically different so if you get stuck, it will genuinely take you hours to figure out the question that you have, if you ever figure it out. In terms of quizzes, we had 45 minutes for a true/false portion plus 3 or 4 questions with 2-4 parts each. All but one will be questions from the textbook, and the questions from the textbook will have at least one new part that you have to do on the spot. True/false questions will mostly come from lecture so make sure you review your lecture notes and not just the textbook. Professor Melcher is great though, super nice, super smart, approachable, just goes a little too fast sometimes. She is vague with the curve (she mentions having 5 different methods), which is frustrating if you're trying to figure out if you're going to pass or not. I'm not sure if I'd recommend Melcher or Saenz; there are flaws in both classes. You'll probably learn more in Professor Melcher's class but you'll probably get a higher grade in Professor Saenz's class. We don't go over any applications in this class at all so if you're a CS major or Engineer this is honestly not that useful of a class for you, except for maybe the first section on Markov Chains. All in all, this class was pretty bimodal in that you will either do very well or you will struggle, and I definitely leaned more towards the latter so my review is biased in that sense; but, I wanted people thinking about taking this class to hear the opinion of someone like me.

Great class, learned a lot, and covered the first 5 chapters of the textbook (Intro to Stochastic Processes by Lawler). The material is very challenging through and very time-consuming to thoroughly understand, but do-able if you like probability and work hard at it. Grading is fair and in your favor for the most part. The other comment sums up pretty well how the course is structured, 5 quizzes based on the HW problems assigned from the book where you can use your HW on the exams. T/F questions can be tricky. Unlike other math courses, stochastic covers applications of mathematics meaning it draws upon ideas from probability, linear algebra, calculus, and differential equations at times to solve specific problems instead of teaching a broad set of related skills. You're basically using ideas covered in previous math classes and applying them to solve problems that arise in modeling random processes. I would really really make sure you understand probability and linear algebra well before taking (calc + diff eq also help but aren't as important).

Definitely a difficult course. Melcher is a good professor though. You need to put in the work to do well. Your grade is determined by 5 quizzes. The nice thing is that quizzes are based on the homework assignment. Melcher posts homework questions for quizzes a few weeks in advance and the quizzes are usually very similar to the homework with a few extra problems thrown in. On quizzes, you get to use your homework - it's not checked. You can write down anything you want on your homework. You only get 45 minutes for each quiz and they're comprised of 10 True/False questions (if you get one wrong you lose 0.5 points, so be careful) and 3-4 more problems from the homework with extra parts added on. The quizzes aren't too difficult if you do the homework, but each question on the quiz is comprised of 3-5 parts. So you don't have much time to look back at your homework, you usually have to just know it.