I will be honest, near the end of the quarter I was quite burnt out and managed to stay afloat pretty much only because of the TA (Smith).

There were ten homework assignments, three quizzes, two midterms, and a final this quarter. The quizzes were worth 5% of our grade each, and we were given a generous amount of time for all of them. Personally, I didn't appreciate the workload, especially near the end of the quarter when I needed to start cramming for finals (one of the quizzes was on week 10), though the homework assignments definitely help with the exams and quizzes. The midterms were difficult, at least in my opinion. The first midterm had an average of about 36.6%, with a cutoff for an A- at 40%. The second had an average of around 31.5% with a cutoff for an A- at 36%. As of this review, we have yet to take the final, but I'd imagine it to follow roughly the same distribution.

Professor Christou is definitely a very competent lecturer, though I think some might find him to be too quick. Do be sure to make use of his many handouts and daily office hours; if you do so and ask questions, you will probably do fine. Though he may seem a little rude or impatient during his office hours, you will probably get an answer to any question you ask him, and he is in general very helpful.

That being said, this course was quite stressful so I wouldn't take it again, though if I ever feel motivated I may take another course with him in the future, since I think I learned a lot from him.

While he is difficult, I would recommend anyone reading this to take at least one of his courses.

If you are a stats major at UCLA you MUST take a class with professor Christou. I know he is tough and you probably heard horror stories about his 20/100 average midterms and finals, but he is the best professor out there. I learnt so much in his class that made me more certain about my academic career! He also cares deeply about student learning.

In general he's also a really sweet human being. He said BLM in zoom lecture and im just 😭😭😭 All fun aside here are some of logistics:

Because I took it during Spring 2020, ie the coronavirus time, classes are held online and format has been changed. We had 10 quizzes in total (the last one is optional). In the beginning they are called quizzes because you only have 45 minutes to complete them and no collaboration is allowed, but after the first few tries Prof Christou decided to the quizzes more like homework on the weekend. They are still called quizzes tho.

We had 2 midterms. The first one is a 2hr midterm with avg at 27. The second one is a 48 hr one with avg around 46. Both are open book open notes. The exam itself is tough, but it helps you learn a lot in the end.

Final is made optional, so I decided to opt out, and I think most students would do so too.

In the end I recommend taking classes with Prof. Christou. If you have a strong solid math base (especially in linear algebra) you will probably struggle a lot less. If you are just looking to fulfill a req and not really looking to learn more about stats, take it with someone else to save yourself the troubles.

Instead of complaining again about the super hard exams that everyone already knows. I would like to talk something else about Dr. Christou. I know that his tests may make your quarter super stressful and all, but if you plan to go to graduate school, you should take at least one class with him. It gives you the taste of graduate school, the "challenging academic life" that you always want to have as stated in your Statement of Purpose. I took 100B and 100C with him. I spent at least 3 hours every weekday to study for his class alone. His tests force you to learn, and sadly, yes, you have to put more priority to his class in order to do "good" on the tests. He helped me so so so so much when I applied to grad schools as he would do to you too if you ask him. That was when I realize how much he cares about students' success. You should not go to his office hour before having already tried your best on the assignments, show him that you made efforts to solve them. Now probably you think that I go to his OH everyday and am his favorite student or something, NO, I barely went to his OH, less than 5 times when I took 100B. If you plan to go to grad school, take a class with him, before you apply, go to his OH to ask for advice, tell him what your plan/concern is.
To those who are applying to grad school in statistics: GPA, major, and whether if you took Math115A/131A/151AB/164 /142 matter the most when you apply.

Christou is definitely not a bad professor/lecturer, but I think he's slightly overrated. His lectures go REALLY fast, so sometimes you have to look at the lecture notes that are posted after class, which can be annoying. Homework was medium difficulty, and the overall workload was manageable.

The thing you need to remember about Christou's exams is that their difficulty is balanced by a FAT curve. The class is medium difficulty, but people think it's really hard just because they get bad scores on the exams. While you definitely have to put in effort to get an A, it's very achievable. Probably my favorite aspect of the course is that Christou views exams as learning opportunities rather than opportunities to punish negligent students. He makes the exams really hard and doesn't tell people the letter grade cutoffs until the very end of the course so that people focus on learning the material rather than achieving X% on their overall grade. If you regularly put in effort, you're pretty much guaranteed to pass the class, even though it might not seem like it.

You can tell that Christou cares a lot about student learning just by looking at how frequently he holds office hours. However, he can often be rude or impatient when students ask really basic questions. To some degree I don't blame him because people sometimes ask things that they could easily find the answer to themselves, but a lot of the time his frustration is unwarranted.

Overall, the main thing I found lacking about the course was that there was too much emphasis on derivation/matrix manipulation and not enough emphasis on the ramifications/interpretation of the results that Christou showed in class. For example, one of the bedrock principles of linear models is that we pick the linear combination of random variables that minimizes the mean squared error. While Christou touched on this briefly, he didn't really go over why this is so important, and mainly just focused on deriving all the least squares formulas. You could easily get an A in the class without knowing how this concept relates to actual statistical modelling, and why it's such a crucial concept to understand. I'm probably being a bit unfair here because I feel like this is an inherent weakness of the lecture format, but it's a flaw nonetheless.

I like professor Christou despite his tough tests. I believe passion is the most valuable quality of a good lecturer, and you can definitely see it in professor Christou. He holds office hours nearly every day, and he is always willing to respond to emails and gives detailed explanations about concepts.

Yes, you can't get an easy A in this class, and yes, you have to spend many hours in this course to master the material truly. But taking 100C with him will help you more than if you take it with a professor that gives everyone an A. Believe me. I regret taking 100A with a very nice professor who gives everyone an A because I later found out I don't master the content in probability theory and encountered many obstacles in other courses that build upon it.

I took this class online in Spring 2020, and Christou is honestly the GOAT. He adjusted the syllabus to account for the online format (got rid of the 20+ homeworks he normally assigns and replaced them with weekly quizzes) and did lectures multiple times a day for people in different timezones. His office hour schedule is legendary; more than two hours a day pretty much 6 days a week if not 7.

This class is not church, you can't get away with going once a week and falling asleep. Tests are ridiculously hard but Christou doesn't treat tests like punitive assessments meant to punish people. Before every test he reiterates that the objective of the tests are to learn new material and apply concepts in different ways rather than just rehash the quizzes/homeworks and he's completely right–I learn a lot and enjoy being challenged by the tests. Pro tip: pay attention in class and take notes, he's a clear lecturer and not everything you need to know is on the handouts. Smith (the TA) was also really good and amde concepts much simpler to understand.

Some parts of the class were in R, but he goes over the code in lectures and if you're taking this you're probably a stats major so seriously–learn R. Those were the easiest assignments all quarter and in my opinion, also the most practical.

Fundamentally, this is a professor who went out of his way to conduct multiple lectures a day, record review videos outlining concepts once a week (in addition to lectures), conduct office hours nearly every day, and made sure to start each class with a preamble about the state of the world–coronavirus, the BLM movement–and reminding us to look after our mental health. He made the final optional and recorded a thank you video at the end of the quarter of himself giving a really inspiring speech in front of the math-sci building. One of the best, most caring professors I've ever had the privilege of taking. Tests are hard and the workload is high, but it's so, so worth it.

TLDR: great guy, nice handout/knowledge, shitty tests and mid-good teaching

No clue how he has such a high rating on 100C (4.6 at time of writing).
He's not a bad professor, he's a pretty nice dude. His handouts are actually pretty good. But that doesn't change that his teaching is average. He loves to overcomplicate concepts and things, and randomly will add some letter or weird notation out of nowhere. He's good at explaining concepts, but often skips steps and may go quickly. He also does encourage questions, which is nice, but sometimes his answers are kind of weird/intimidating.
His tests are tough and challenging. And at times, you just hope you can scrape partial credit. His handouts are fire, but his tests suck. Our midterm had average of 25%. The tests ask questions that are so tough and alien as if it's from another class sometimes. If his tests were somewhat similar to the handouts, it would be so much better. The test is basically impossible to completely finish, it is very long and "is meant to challenge you". But it is tough to be challenged if you are clueless.
He obviously is pretty generous in his curves (which is why I'm guessing some of these reviews are high). I think around 50% get A to A-, and similarly for Bs. I don't think he ever fails anyone.
Other notes: he always prints out the ~100 pages (single sided) handouts, it is up to you to take it. You have to go to class to know what is happening and it's not recorded/never posts class notes

Christou is incredibly clear, and if you don't get something he'll explain no problem. Homework you definitely have to block off a good amount of time each week to do it, but office hours are super helpful. And there are OH every single weekday and some on the weekends too. Tests are difficult and demoralizing but he curves the class. Christou wants you to learn over stressing about grades, and he does that by challenging you. Through this course, he really hammers in fundamental statistic ideas. If you have the time in your schedule and genuinely want to have a good statistics foundation, take Christou. He's also great at trying to build community in class and is funny too. Great deadpan humor

I took STATS-100C in the summer of 2023 as an international student. Overall, I would unequivocally state that Dr. Nicolas Christou is undoubtedly the BEST professor I have ever encountered, and there's no need for the qualifier 'one of' before that.

As a general overview, at the outset, the class had approximately 15 students (if I recall correctly), but by the end, only around 9 students persevered and took the final exam. Throughout the course, we had 2 quizzes, 1 midterm, and 1 final, all of which were required to be completed on-site. The examination time was limited, and most of us couldn't finish within the allotted time. The class average hovered around 25% for each exam, and achieving an A required consistently higher grades.

Dr. Christou's class is undeniably one of the most challenging courses, demanding extensive matrix calculations, theoretical proofs, and particularly, a meticulous attention to numerous but exceedingly crucial details. Mastery involved step-by-step proofs and meticulous result comparisons, constituting the sole pathway to familiarity and comprehensive understanding. However, speaking as a senior statistics student, I personally consider this class pivotal for grasping concepts essential to advanced courses, predominantly centered on linear model frameworks like econometrics, sampling surveys, multivariate statistics, etc. Personally, I find this class the most captivating among all proof-based classes. Therefore, I wholeheartedly recommend anyone interested in statistics to enroll in this course!

Regarding Dr. Christou's mentorship, I can't express enough gratitude and admiration. He holds office hours for nearly 2 hours every day, six days a week, simultaneously available on Zoom and onsite. He consistently offers assistance and willingly discusses all our concerns. What struck me profoundly was his insights on linear models. To reiterate, don't confine yourself to comprehending only the handouts and his questions; I strongly recommend engaging with him in his office to explore lecture topics more deeply by sharing your comments and areas of confusion. Doing so significantly contributes to clarifying concepts. His profound understanding of linear models and enthusiasm to share insights are recommendable!

Regarding linear models themselves, I have several suggestions for your consideration. Broadly speaking, our work revolves around the linear model framework: estimating parameters to render this 'model' usable (and assessing the degree of confidence in these estimations, which entails statistical inference), and ultimately, applying this usable model for predictions and other advanced goals.

Firstly, from my opinion, commencing from the perspective of 'uncertainty' and dissecting and elucidating information from it could serve as an engaging approach. To elaborate, starting from the disturbance term ( a random variable we encountered in 100B, hopefully), and utilizing additional covariates (i.e., the X variables) to segregate fluctuations, we can explicate, quantify, and comprehend a portion of the uncertainty based on 'correlation,' which facilitates subsequent predictions.

Secondly, it's crucial to remember that the linear model itself is solely a 'framework.' Due to unknown parameters, it remains 'unusable' until the estimation process concludes. This 'reminder' has been beneficial to me, at least. Furthermore, only upon completing statistical inference can we ascertain the quality of this estimation and subsequently gauge our confidence in the results, i.e., the estimated y_hat (a side note: it is a random variable).

Furthermore, as a final reminder, I strongly suggest you to thoroughly grasp the single linear model, the foundational model presented in his lecture. Subsequent learnings merely entail slight variations on this baseline, notwithstanding potential difficulties in complex matrix calculations. Maintaining a focus on the 'Big Picture' and understanding our position within it would help in recognizing similarities and differences between methodologies. And once again, I strongly encourage you to enroll in this class with Dr. Christou.

Wishing you all a fantastic and enjoyable journey in the realm of Linear Models! Best wishes :)

This class is TOUGH but so worth it. The homework is pretty hard and the tests are even harder, but Christou is very fair with his curving and tries to help his students learn as much as possible.