- TAKE IT! It's so useful. People aren't lying when they say this is one of the few courses that you'll take that you will use in your future job. The content is difficult, but Duncan does an amazing job of making sure you understand and that if you don't there are resources to reach out to. TAKE IT WITH HIM.
- Take it with Duncan if you want to do anything involved with research. And take it early.
- I envy you. I am devastated to think that the semester is over and therefore this course is over. I would give anything to start fresh and have the experience of taking this course again. If you give it your all, this course will give you everything back. Some advice: go to every class, go to office hours often, start the problem sets early, and importantly, try to go into the course with a positive attitude. It will be hard-but it will be the best hard thing you'll ever have to do. Genuinely.
- It is very difficult so be prepared to work hard. Doing the problem sets can help you learn the materials because it is hard to follow along in class if you don't have a strong stats/econometrics background.
- Take this course if you're ready to put in the work: it's challenging, but the lectures, problem sets, and discussions make it one of the most rewarding classes you'll ever take.
- If you want to think like an economist TAKE THIS CLASS W/ PROF THOMAS, it's challenging but it's so worth it.
- Do not get behind.
- It's harder than 104
- Workload and content is challenging and this should be accounted for. Should be dedicated to class and review material consistently.
- I would say that it's not "easy" but that's because it's not meant to be and if you go to lectures and everything you'll be fine
- If you are willing to learn and put effort into getting better skillsets for research, definitely take it with Duncan Thomas. It is not an easy class by any means, but it is the most rewarding and useful class at Duke. Duncan's philosophy for education is unparalleled - he really tried his best to provide students with values added and my conversations with him made me reflect on the qualify of the college education I have gained because he is just so so great. Duncan is truly the best instructor and lecturer I have ever encountered, I am saying this with lots of love and respect.
- This course is tough, and not fun, however you need to know the concepts taught if you want to be successful. I talked about my experience with STATA and class problems sets in an interview for Amazon and got the job
- this class will challenge you, a lot
- It is hard and requires a lot of effort. The professor is not understanding about missing class (even if you are sick) or arriving a few minutes late - if you miss a pop quiz because you were 5 minutes late, but attend every lesson in the semester, your grade is hugely impacted. However, you learn a lot, and makes you think critically.
- It may be tough, but it is super valuable to learn metrics and data science!
- Take it with Duncan Thomas.
- The course is hard and at times extremely frustrating, but worthwhile in the end. Put in a lot of work before the midterm to save yourself some stress, and make sure this is the hardest class you plan to take for the semester. You will learn a lot if you are willing to dedicate 10+ hours a week.
- It is a lot of confusing and difficult work, but when you finally understanding something it's a good feeling. Just buckle up
- don't fall behind!
- Take it with Duncan only!
- Do not take it unless you will go to every lecture
- Pay attention and engage in class -- that'll go a long way.
- Definitely take it! It is difficult but so rewarding!
- TAKE IT. This is arguably the most applicable course in the major and the most interesting and Duncan is the best professor for this class without a shadow of a doubt.
- Pay attention at every moment.
- if you really want to learn econometrics: you HAVE to take it with duncan. you'll come out as a much academically inclined student, and will love it. take it early in your time at duke! there are biweekly problem sets, occasional quizzes (they're not too bad) and lots of discussion in the classroom!
- Review the slides before you do the PSETs
- N/A
- Definitely to keep up with the work, review each of the slides after every class, ask for help/ask questions when you don't know something.
- This class requires a lot of outside work. You will have to go over topics on your own.
- Difficult, but worth it you want to understand econometrics
- It is tough, be ready. Great class, just attend, pay attention, and have a good study group.
- This is not an easy class, but it is a great class. It is known to be hard, but it is incredibly engaging. Professor Thomas does a great job of making the class more than just a lecture. It is often a discussion of the material amongst everyone.
- Take this class very seriously and you will learn a lot from it
- Make sure to come to class on time, otherwise you might find yourself 5 minutes late and missing a graded quiz, and there aren't many quizzes given and I don't think any are dropped. The homeworks are pretty fun, and not too math heavy, they focus more on Stata and economic intuition. The tests are graded a little harshly, but the concepts are very interesting. Overall a very good course.
- Take it with Professor Duncan Thomas. Though the course might be hard at first, if you do the work and attend class, your grade will be strong. More importantly, you will develop the proper understanding of data and research that translates to any career. Interviews and research positions ask questions that directly come from concepts in this class. It will definitely enhance your understanding of data and your ability to make data-driven decisions.
- This will be a hard and time consuming course, but it is really worth it at the end. Duncan is an amazing professor and you will gain so much knowledge that applies to the real-world. Make sure to stay on top of the work and actually participate in class, it really helps.
- be prepared to put a lot of your own time into understanding concepts
- To commit their full attention since the beginning of the semester to not fall behind
- Even though the content is very challenging, the practical value of this class makes it worth it
- Fine to take it with Duncan, grade just comes to midterm and final. He clearly cares about the material and knows a lot with interesting applications
- do not take unless you have a true passion in statistics, have alot of knowledge coming in, or is required for major. as someone who has no interest in statistics, felt like I took this class only to fulfill Econ credit
- Make sure to set your schedule around this course, it is very difficult to take this well if it's not your first priority in the week.
- Take it - it will be very difficult but rewarding.
- Understand that this class will likely be more challenging than taking it with Professor DeSimone. Professor Thomas is extremely knowledgable, but that sometimes comes at the cost of him not understanding that you don;t always understand, so speak up when you have questions. The real world applications of this class are great, but you need to be willing to put in work to get something out of it.
- Treat the course seriously. For the sake of your own learning, but also to respect Professor Thomas, who works very hard to make it a good course. I always dislike when people do not take a course seriously when they have a very good professor, as that leads to the professor feeling disheartened. And, we end up with worse courses as a result.
- It is very challenging and goes very fast, make sure to maintain engagement especially in the first half of the course. Ensure you have good foundational knowledge of statistics before taking
- I would say the horror stories about econ204 are a bit overblown. As long as you pay attention and make an effort it will not be overwhelming. In fact, it is often quite interesting and applicable to many fields--even as a non-econ major I found it useful.
- take it only if you are willing to give 100 poercent effort
- The course is extremely challenging, so dedicate enough time in your schedule to work through problem sets and actually challenge your understanding of econometrics. But definitely a class that improves your critical thinking skills and hones a conceptual understanding rather than memorization.
- Best class I have ever taken at Duke. If you want to learn econometrics and push yourself, take it with Thomas.
- Go to class and do the problem sets.
- This is a hard, challenging class but so interesting. It is the most applicable class you'll take in Econ. Expect challenging content, homework, and exams all throughout, but don't postpone this class just because it's hard. It's a good and valuable challenge for anyone (just don't take it alongside any other hard classes).
- Take this class in the fall with Duncan Thomas! It is rigorous and you must be diligent about spending time on the class outside of lectures, but you will learn alot and build intuition in a short semester.
- Make sure to be consistent and be prepared to work hard. It is not an easy course, but you will learn a lot. There is a lot of additional help available in the form of office hours so make sure to utilize that.
- I hope the TAs in that edition of the course are great because they drive a huge part of the learning in the course.
- Pay attention in class and review the notes after lecture!
- N/A
- it is defintiely a hard course so be prepared
- 1) Make friends with your peers. 2) Attend TA and Office Hours to better your understanding. 3) Review content after class.
- Professor Thomas really cares about his students when he feels they are putting in as much effort as he does to his lectures. If you are very interested in learning regressions and are willing to dedicate the necessary effort and time this might Duke's best regressions class due to how it builds your intuition when working with data in real-life settings. Nonetheless, the class requires a lot of work with the amount of content covered, the problem sets, and the difficulty of the material. If you are not a quantitatively oriented student who does not want to dedicate that much effort to Econometrics I would avoid taking this course in the fall. Professor Thomas has a very particular way of conducting class which you will have to adjust to if you take the course with him.
- Taking it with Duncan Thomas is very worth it. It's difficult but you will come away with a distinct appreciation for what you can and cannot do with data, and how it all hinges on what assumptions you make.
- Definitely take it with Professor Thomas if you can. He only teaches it at 8:30, but he makes the class fun and engaging. His policies are more than fair, generous, and he is always happy to explain things when asked.
- It is going to take several hours outside of class to do well.
- Do not take this course with Duncan. Do yourself a favor and take this course with Jeff DeSimone. I have thought that all the talk about Duncan's class being hard had been due to the subject material, but it was truly just due to an extremely frustrating grading system and terrible course policies. I spent an incredible amount of time on this course, but because of how he structured his class, it truly did not matter. I truly regretted taking this course with Duncan and should have listened to everyone who told me to take it with Jeff.
- If you care about your GPA, don't take this class. If you are deeply interested in learning econometrics, though, do take it. Before the semester even ended, I had potential employers asking about my econometrics skills in interviews because of how eager they were to see I was learning this material. This is an awful class to take while overloading, no matter how easy you expect the other four to be. Duncan Thomas is an awesome instructor, but he has no patience for students trying to get the grade without putting in work. Also understand that ECON104 needs revaluation as a class-
- over the last three semesters, students have had wildly different experiences taking it. Make sure you are fully prepared to take this class and think critically about whether your 104 section equipped you well, or if you need to do some additional review/studying before signing up for 204.
- Don't be late to class.
- If you don't have to take the class, take it. If you do take the class, please take it with Duncan Thomas. A difficult class yes, but one of the most rewarding and thought-provoking classes during my time at Duke.
- If you're taking it with Duncan, don't give him a chance to dislike or develop a negative perception of you, because in my experience, it was hard to change that

- Learning to think economically, learning to reach out for help and to utilize all of the resources I have, and to cooperate with my fellow classmates.
- Linear and multivariable regression, causality techniques (instrumental variable, regression discontinuity), and intuition behind concepts
- advance coding in STATA, learning about causal methods, using different statistical methods
- I learned to think in ways that I didn't think were possible. Every class period, I left the classroom knowing something more about how the world works. I leaned lots of practical skills (some coding with STATA, how to run regressions, how to assess econometrics papers) but more importantly I learned how to think about new problems. This class is all about using concepts you've learned to discover new ways of solving a problem.
- Types of regression estimators How to estimate causal relationships using a regression model Hypothesis testing
- I learned how to approach data with precision and rigor, combining theoretical understanding with practical application. I gained a strong foundation in regression analysis and hypothesis testing, learning how to derive insights from complex datasets. Most importantly, I developed the ability to think critically about causation and correlation, equipping me to analyze real-world problems with a data-driven mindset. Professor Thomas's clear explanations and thoughtful guidance made this course outstanding I couldn't recommend it more highly.
- Regression, Causality, significance testing
- I learned a lot about correlation, covariance, and the relationships between variables
- Econometrics and regression making
- I learned the more advance foundations of econometrics. My STATA skills improved and became more effective and nuanced. My wider application of statistics and econometrics to real life context improved.
- Understanding how to statistically interpret real world phenomena.
- 1. To be very skeptical of any statistical research or results I ever read about because I have a clear understanding of the various assumptions that must be made to reach the conclusions and how easy it is to manipulate data 2. Learned all about statistical analysis and the ways we can use it to understand the world 3. Through the problem sets I actually learned interesting things about various social issues like wage gap, impact of being an athlete on grades, etc etc
- Different regression estimators, Big 4 assumptions, how to establish causal relationships in statistical analysis, economic theories This class provided the most solid statistical foundation ever - allowing me to use STATA sophisticated and approach large datasets in a structured manner
- How to use best judgement in stats and how to use Stata
- Learned about how to interpret statistical data, how to verify the claims of a statistical finding and various ways to construct our own models
- statistics, math, regressions
- Critical thinking, intellectual stimulation, intuition. Regression (mostly focused), statistical significance, hypothesis testing.
- Linear regressions, data analysis, logical thinking
- Technical skill --> STATA Way of thinking --> Not being phased by complicated-looking math equations, overwhelming symbols Insights --> Econometrics is relevant to the real life.
- I learned how to use economic models and interpret data, how to understand the math behind regressions, and multiple different forms of regressions to determine causality.
- Econometrics, STATA, more econometrics
- I learned to identify causal relationships, use nonparametric methods, and evaluate the evidence in economic studies.
- All sorts of metrics! Regression stuff like grouped data, fixed effects, and IV estimation
- I feel that the biggest thing I've gained is a more quantative/analytical way of thinking that I've gained though this class
- Econometrics, data analysis, regression
- Regressions
- R, Statistical Testing, Being confused
- 1. Regressions 2. Correlation 3. Bias
- This course developed introspection and deep thought. It teaches students how to draw their own conclusions and opinions, through out of the box thinking and creativity.
- I learned about regression, modeling, testing, and making sense of data.
- OLS Regressions, Causation, Standard Error Estimates
- causality testing methodologies and models like RDD, DiD, FE etc, classic linear regression but also medial regressions, mle, bootstrap, jackknife and a lot more. most importantly, critical analysis and research analysis skills.
- I learned a range of statistical methods - regression theory, exploring causality in econometrics, and coding in Stata
- Statistics -- Regression, Causality, Multivariable Regression.
- Prior to taking this class, aside from the basic regression, I did not have any of the skills that we learned in class such as running a regression, coming up with a model, OLS, LOWESS, instrumental variables, fixed effects; not only did I learn these things and have a better understanding of what they were, I also am comfortable with using STATA. Even though we used it a little in Econ 104, I did not really understand it while I was using it.
- I learned about causal relationships, how to use stata, and that I need to sit in the center to stay focused
- - Econometric Analysis - Applicative data analysis - Econometric intuition and interpretation
- How to interpret data, fit data, ways to evaluate data
- Basic statistics, regression models, hypothesis testing, causality, and real world examples.
- Different types of regressions, how to determine causality, hypothesis testing, multicollinearity, and more.
- I learned about linear regression models.
- Think more critical about empirical evidence
- We learned how to apply econometrics methods to real world datasets, doing things like regressing to understand the relationships between variables, instrumental variable estimation to move toward causal estimates, and manipulating input and output variables to represent new features of the data we were looking at. We also learned the theory behind the statistics and econometrics we were learning, deriving the underlying equations and building intuition about correlation coefficients, R^2, and different test statistics.
- I developed a strong intuition for data analysis, something has been super valuable in my research and other experiences. I learned how to make decisions based on existing data, and how to set up models to predict certain things or give them causal interpretations. The instructor was very good and effective in instilling the correct intuition. This class was the most relevant class I have taken at Duke.
- Intuition behind statistical methods and interpretations, how to look through data and effectively analyze it to arrive at conclusions, how to deal with violations in assumptions (such as heteroskedasticity).
- I learned how to interpret data, where data might be missing information, and the whole story.
- my skills using STATA developed during this class as well as applying economics to real life situations. this course also challenged how I approach answering questions
- I learned to think about how factors can hold an isolated weight on an outcome, how to establish causality, and about the importance of analyzing error terms.
- Economic intuition/rationale
- 1] Ordinary Least Squares Regression 2] how to choose a model to fit data 3] Least Absolute Deviation
- How to use statistics in looking at the broader world
- I learned what regressions were (my understanding was very limited before this). I learned how they worked, what kinds there were, and how they to account for various types of statistical issues.
- I learned how to analyze economic questions and apply different statistical models to observe the differences in results, I learned multi-variable calculus in the context of deriving economic concepts, and I learned how to use Stata.
- I learned a lot about ways to apply econometrics to the real world. I learned so many applications in fact that I think I will struggle to remember them all, but some of the few that I think will be very helpful in my future endeavors would be OLS, IV, and fixed effects for sure, especially with my job as an RA at the DEAL. With how difficult this class was for me, I also unintentionally learned about time management and collaborating with others to problem solve as well.
- Broad thinking about how, and why to apply certain data analysis techniques.
- Statistical inference in the field of economics, regression analysis, how to use statistical software
- regression and interpreting results, hypothesis testing, ways of controlling for bias (fixed effects and instrumental variables)
- learned how to 1. think analytically 2. consider extraneous factors 3. model the relationship between different variables and draw conclusions
- I developed a more comprehensive of econometrics than I did in Econ 104. This course truly challenged me to have an intuitive explanation for statistics beyond the formulas I'd simply memorized before. I learned to think critically about study designs and weigh various statistical results to form my own interpretation of the data.
- 1. Quantitative analysis 2. Data analysis 3. Analytical thinking
- I gained a lot of econometric knowledge, ability to focus on a task, time management skills, precious insights into looking at real life events and interest in stats and econometrics.
- I learned many tools on how to analyze data.
- How to use regressions and apply them to real-life data, how to consider causal relationships and their intricacies, how to critically analyze data and consider its relationships.
- 1) regression models 2) relationships between data 3) stata
- Advanced econometric methods, how to analyze regressions for causality, how to build models with different dataset characteristics
- Critical thinking, building intuition while thinking about real-world problems, the importance of consistent hardwork
- OLS, LAD, MLE
- how to identify causal relationships, how to control for confounding variables in an experiment, how to look at information in general
- learning mathematical derivations of stats formulas building intuition on formulas understanding experimental design
- 1. How to apply stats/econometrics to real-world scenarios (psets and class examples) 2. How to interpret statistcal results 3. How to use tools like stata to find relationships in data
- Not good
- How to use STATA, how to conduct OLS regressions, how people try to establish causality
- Regressions Use of data in economics What economic research even is
- I learned the value of interpretation and being rigorous about choosing methodologies when analyzing statistical data. I learned about how to derive causal estimates under both true randomized conditions and non-randomized conditions and a framework evaluate different options. I learned to be skeptical of economic research due to being exposed to many methodologies that can be misapplied to try and force seemingly conclusive results.
- Econometrics skills needed to succeed in the workforce and in other areas not specific to economics.
- Learned about residuals, means, and different analysis methods.
- I learned about residuals, means, and different measures of analysis.
- I learned a bit about statistics.
- Builds an in-depth understanding of econometrics foundations and prepares you well for applying statistics/econometrics to undergraduate economics work. In this class, I improved my understanding of how models are constructed, how we can assess the meanings/impacts of models, and what key assumptions we make about our models.
- fundamentals of econometrics, statistics properties, how to apply knowledge of economic theory to be critical of econometric research and model design
- OLS, causality, instrumental variables
- Questioning the underlying assumptions that go into different methodologies, building intuition regarding mathematics and econometric foundations, and navigating different problems through multiple lenses.

- Genuinely Dr. Thomas was an amazing instructor. Whether that was making sure that we were all listening during class by asking out classmates to explain things to us, or that was through having multiple office hours from himself and his many TAs, or that was through offering all of the problem set answers and course materials on the economics course website the moment after things were due, he was an amazing instructor and while this course was probably the most complicated and difficult course I have taken at Duke I don't think I've had so much fun learning in a long time.
- Lectures themselves are the best
- This class offers countless opportunities to interact. Prof. Duncan asks questions and makes sure you're following the material throughout the class, the TAs follow up on questions you had during office hours and your peers are genuinely willing to work with you to help you understand concepts. That's because Prof. Duncan grades the class in a way that does not encourage competition but cooperation between students. Also: - Great slides to refer back to - Useful low-stakes quizzes to consolidate concepts - In-depth problem sets that make you think deeply - Great weekly TA review sessions
- In every sense, this course is the best I've had at Duke: Professor Thomas delivered the strongest lectures I've ever attended, with his engaging style making even the most complex concepts feel intuitive and approachable. His problem sets also stand unmatched in their thoughtful design and ability to teach relevant material in fascinating and creative ways. The discussion sections are the best I've experienced so far: each and every TA was incredibly knowledgeable, and they all pushed me to think deeply while offering explanations that could've belonged in a textbook. Even as a student, I could tell that Professor Thomas had to handle more than his fair share of challenges from my classmates who weren't fully engaged, yet he never let that disrupt the class's positive learning environment or diminish the experience for those who were eager to learn. This combination of brilliant instruction and course design made the class a truly standout experience, and I couldn't be more grateful.
- The class is very conversational, so Prof Thomas allowed us to try and solve the problems eventually allowing us to get to the correct solution. This also allowed us to understand better why some things work over others. This class was super engaging, even at 8:30, Prod Thomas always captured everyone's attention. It was also super applicable to the real world, and pretty much all of the in- class and problem-set questions were based on real-world data. This is not the type of class where you memorize, but rather build intuition and language that economists and researchers use, by far the most useful course in the econ sequence.
- The layout of the classroom was nice. I like that it was not in a huge lecture hall
- Very thorough lectures and good TAs.
- Problem set structure biweekly allowed for a reflection of content learned. Class structure of PowerPoints and interactive nature was highly effective.
- Very engaging and cold calling which helped me feel engaged in the class.
- I fed that the professor would call on people and encourage questions, he also never made anyone feel stupid for a bad question. By the first few weeks everyone felt comfortable being vocal
- The problem sets were challenging but gave me enough practice to extract insights from real-world datasets. The lectures were engaging and interactive - my most focused 8:30 ever. Duncan's office hours were immensely helpful. He is truly caring and is willing to go over any question thoroughly. I appreciate that he stayed very late sometimes when there were a lot of questions from students.
- Posting the slides after class and keeping all students engaged
- The professor would cold call the class questions on the lecture - made me a very active listener
- good learning environment with high class engagement
- I enjoyed the problem sets - although very long, they allowed better understanding and consolidation of material. Professor Thomas emphasizes very important intuition.
- Duncan was incredibly engaging and the lectures were really helpful. Loved the examples given in class to describe the concepts.
- The pop quizzes are good incentive to show up to class - I wish there was more clarity on how many exactly will be dropped. Keep for future years: extra credit oppurtunity, oppurtunity to replace midterm grade with final.
- I enjoyed the class structure with Prof. Thomas constantly asking questions and ensuring we understood things. I also thought the review discussions were helpful.
- He likes to have a high level of engagement in the class
- The problem sets were very well-designed and made it easier to understand the most crucial concepts from the class. They were really helpful in building intuition and preparing for midterms.
- Lecture was really engaging and the problem sets did a good job working back through all the material and explaining it again
- The instructor did an excelent job faciliating learning. No phones/computers, called on students randomly..
- Interactive
- Duncan was kind of funny, the topics were very dry
- I like how interactive the lectures were, I thought it was too early in the morning though
- Instructor's lectures were very engaging. His memorization of our names and cold-calling showed that he cared a lot too. Problem sets were timed reasonably. Support was great.
- The instructor used cold calling to keep the class engaging and insightful. This was the most productive class I have been a part of! I loved it!
- The interactive presentation style helped me stay engaged and the homework assignments were completely application-based.
- Lectures followed by discussion sections backing material up.
- duncan is just amazing. i can't imagine a single professor who can teach such a quantitatively intensive course with such lucidly clear instruction and intuition. the cold calling is really intimidating initially, but once you get used to it, its great. he doesn't humiliate or shame anyone, you're welcome to make mistakes, and that's the best part. you learn so much if you engage.
- The TAs are amazing for homework help!
- N/A
- I actually really liked that we met at 8:30 because it would be the first class I would take of the day, which meant that I was able to fully pay attention to the content. I also liked how Professor Thomas suggested that we look over the slides after every class because I followed that and it helped me stay up to date with all of the content. In addition, I liked the pop-quizzes because I liked not knowing when they were because that meant that I had to keep up with all of the content which helped me from falling behind.
- He made is lectures a conversation between student and professor. Although this is stressful, it insures that you pay attention and create some sort of relationship with your professor.
- Lectures were good (just at 8:30...) Sometimes went too fast, but interaction with questions was great during lecture
- In person quizzes and interactive lectures
- I enjoyed the lectures, he is very engaging and I believe goes at an appropriate pace always leaving space for asking questions.
- The class was probably the most engaging out of all of the classes I have taken during my time at Duke. Professor Thomas made it a point to learn everyones' names and call on people to finish out his thoughts, answer questions, or help answer other people's questions. He fostered an environment where most if not all students felt comfortable asking questions which helped everyone's learning. Great office hours schedule as well. TAs were all excellent which made everything much easier.
- N/A
- I think the professor did a good job engaging the class while teaching econometrics methods, by building relevant examples that students could follow easily and by including students in the lecture with frequent questions. Additionally, having two weeks to complete homework let me really learn the concepts, rather than just scrambling to get answers in time for the due date. The professor built very good slides aimed at giving students intuition about concepts like multivariable regression and fixed effects modeling.
- The instructor was very engaging, and purposely made decisions that benefitted the learning of the entire class. The professor, despite having a class of over 100, tried to engage each and every student by learning each student's names, calling on kids to help one another out, and asking questions to students who seemed like they were struggling. I would keep the way the course is taught.
- I think this course was great overall, a lot of accountability and responsibility with a lot of support and excellent teaching. Definitely one of the best taught and most useful in the real-world courses here at Duke.
- Office hours, problem sets.
- By doing in class quizzes he made sure that you were engaged so I would keep those
- I believe the course is well organized and structured. The professor clearly has been teaching it for years and knows very well what he is doing.
- Professor Thomas was always very clear when explaining new topics
- Undergrad TA office hours were super helpful for understanding the problem sets Cold calling in class kept us engaged
- teacher was very knowledgable, definitely keep the professor, but way too hard.
- I really enjoyed the problem sets being due once every two weeks. It allowed me to focus on other things when I did not have time and made the flow of the class feel more flexible.
- The instructor facilitated learning by providing lots of TA and office hours, as well as posting all notes and previous problem sets/midterms on-line. He provides all the resources available to be successful. I would keep things in the same manner.
- Prof. Thomas's method of cold-calling definitely keeps students on their toes and is an incentive to pay attention. I think that his powerpoint presentations are full of information, and that consulting them after class is helpful.
- I liked how the focus was on understanding the theory behind the statistics, rather than a "just because" type of course.
- Biweekly problem sets were at the right frequency to keep me engaged with the material and ensuring i didn't fall behind
- The class was very interactive, Prof. Thomas was great about asking questions and keeping everyone engaged. The course website was a very helpful resource.
- he went through the derivation of each theory used which helped me build an intuitive understanding of the material
- The problem sets specifically were extremely challenging but definitely encouraged me to think more abstractly. They were useful in applying what we learned in class to analyzing a real data set and understanding the practical applications of certain methods.
- His constant discussion type lecturing kept students on their toes and constantly engaged.
- Prof. Thomas is really clear and helpful. He calls on students to make sure everyone is on the same page and he does his best to interpret our answers and answer them.
- Cold calling in class / in-class quizzes encouraged attendance and paying attendtion in class.
- Professor Thomas is great. He explains super well, answers all questions with an impressive amount of patience, and is clearly very knowledgeable regarding theory, applications, and math behind Econometrics. I wouldn't change the method of teaching or the content, as it is highly valuable for Economics majors.
- he was engaging however it was too time consuming for a class with not much practical application
- My instructor made the class extremely engaging. He asked questions frequently in the class and memorized everyones name.
- Interactive and engaging lectures. The course has wonderful support in the form of office hours and discussion sections.
- TAs Angela and Tulio are exceptional. Undergrad TAs are also great
- Duncan Thomas is perhaps one of the most knowledgeable professors I have ever met. We covered a lot of content so for obvious reasons, we moved very quickly, but he was super engaging in how he answered each and everyone of our questions during class. I also appreciated how he explain concepts using relatable examples, such as sophomores vs seniors taking the class or how factors can impact lnwage.
- yes, i loved the interaction between the prof and students. He kept us engaged
- Duncan did a good job providing a lot of practice material via psets and lecture slides. I like how much he engaged with the class and called on people.
- Not good
- Lots of TA help which was reassuring
- 1) He's a phenomenal lecturer, clearly a best in class educator and wants students to learn. 2) The problem sets were incredibly helpful in confirming understanding and linking the theories to the real world. 3) Handouts and course materials were great.
- I would definitely keep Professor Thomas's structure when explaining new concepts. I also think that being very strict with regards to technology and making the lectures very interactive work well together to keep students engaged during lecture.
- I liked how there were periodic quizzes in class throughout the semester, they incentivized you to actually come to lectures and force you to stay up to date with the content in the class.
- Asked interactive questions throughout lectures.
- Professor Thomas keeps students on their toes with his lectures and requires full attention in class. The pop quizzes are a good way to ensure attendance throughout the semester.
- N/A
- Instructor cold calls on students. A lot. Which isn't fun at 8:30am. But, it does create some pressure to pay attention and study with consistency. The wide variety of office hour time slots that the instructor makes available (both with him/TAs) also provides students with an abundance of chances to get help. They just need to seek it out. I would keep the things outlined above for future years. I also liked how problem sets had very apparent applications to the real world.
- bi-weekly problem sets, office hours, TA sessions
- biweekly problem sets, good at explaining concepts and answering questions
- Professor Thomas's speaking, class structure, preparation, and sheer knowledge truly elevated this class to a level making it far outshine the rest of my classes thus far and most likely in the future. His tenacity for his students' understanding is unmatched and truly encouraging when going over difficult topics. The cold calling keeps students on their toes and the understanding ensure that student's feel confident enough to attempt an answer.
- The professor's emphasis on attendance policy and making lectures interactive created an environment that helped boost engagement in the course.

- Nothing. I think the only thing is if ECON 204 was covered by Ecoteach so that it would be less daunting to reach out to the classmates to study together, that would be amazing.
- Not 8:30
- More interaction from some students. This is not Prof. Duncan's fault. Some students take this class, realize it's hard and then hold a grudge against it the whole semester. I feel sorry for them. You will enjoy this class so much if you only trust Prof. Duncan and lean into it.
- The problem sets were extremely long but I can't say for sure if I'd change anything about them other than make them shorter/easier
- There's truly nothing I would change: it was a phenomenal learning experience from start to finish. Professor Thomas's ability to connect theoretical econometrics to real-world applications made every lecture feel incredibly relevant and engaging. His dedication to student success, from his detailed feedback to his willingness to clarify challenging concepts, ensured that everyone could thrive in the course. It's hard to imagine how this course could be designed or executed better.
- It was difficult to keep up at the pace of the lectures. I really think that including them before so that we can take notes with the slides or just being able to have them before lectures would have helped. I understand why it was not that way but it would have been helpful
- Not being at 8:30
- Speed of the class was very quick and made it challenging to follow at times.
- I think everything is taught in a very statistically based manner where it could have been a little more intuitive.
- Going through the slides swear and especially in the beginning of the semester going through things slower like the proofs. And making it clear that we don't need to memorize the proofs.
- It is very very well-structured.
- If the slides posted were more coherent and potentially shorter
- It would be helpful to have access to the slides the day before the lecture so that you can have a basic understanding of the content, posting textbook chapters to read or YouTube videos would be helpful as well
- not being at 8:30am in the morning would make it easier for me to pay attention
- The pace of the class is fast, so I got lost easily - reducing the pace would reduce getting lost. Also, perhaps use the discussions for revision and answering questions instead of reviewing psets because we already have the answers for the posts so discussion on it is not really needed. The quizzes were NOT representative of the efforts/capabilities/attendance - if you arrived 5 min late and there was a quiz but remained in class for the rest of the class, you lost many points off your quiz which counts 15% of your grade. Professor Thomas is NOT understanding about missing a class (even if you are sick) or arriving a few minutes late - if you miss a pop quiz because you were 5 minutes late, but attend every lesson in the semester, your grade is hugely impacted. I don't think this is fair because your grade on quizzes does not reflect effort/capabilities/attendance. For example, if a student who constantly miss class (ex: miss 50%) is lucky to be in class when there are pop quizzes, they get 100% while another student attends 98% of class and arrives 10 minutes late twice and misses pop quizzes that are worth more (ex: 5 and 7 points), they score 50%, which is totally unfair.
- I feel like the discussions could be a bit more interactive, but the TAs were great.
- Maybe in class questions to complete - then we go over it. Just as a hard skill check.
- Problem set was structured a little too complicated - instead of solving multiple individual questions we had 2-3 questions with sometimes over 10 different smaller questions in it, and most times we had to go all the way back to the first small question to solve the ones on the end, which made it really hard to navigate through the problem set, especially when I already forgot what was going on on the earlier sections
- The first part of the course (before the midterm) was difficult to follow, especially when trying to keep assumptions straight. It might be helpful to have a chart in the corner of some of the slides to make it clear to students which assumptions were part of the current estimation model and which ones had been taken out/were based on mistaken intuition.
- Not much, it was very refined. 8:30 sucks though, especially in Sanford.
- Not necessarily professor Thomas's fault but I felt he catered class lectures towards the highest acheiving stduents. these students happened to participate more so it is understandable that it worked out this way
- less problem sets
- Less homework
- Do not do it at 8:30am. Less PSET emphasis on R
- It went a tad fast for my liking. Sometimes too granular too.
- I think the only way to improve the class is making problem sets smaller in size, but more frequent (ie every week). This allows for a more consistent work flow.
- Having more group work during discussion sections would be helpful rather than just lectures.
- Less time reviewing problem sets in discussion and more time attributed to lecture material
- a smaller class size would be great and more applied stuff post causality!
- This course is close to perfect - not much I'd improve. One thing is the length of the problem sets - good for learning but impractically long at times.
- More resources for reviewing content beyond the slides -- I understand that the professor wants people to come to class, but when it comes time to review for the midterm/final, it is hard to recall/review topics just based on the slides. More context, whether recorded explanations or lectures would be helpful.
- I would have loved learning more about how you can come up with a causal effect rather than just correlation because I feel like we learned that part towards the end half of the semester, and I woul have liked to learn that more early on within the semester.
- I think this class should have one day of all econ 104 review. I do not think the unit handouts were necessary. If I needed them I could find it online. I think the course was a little fast and could use required discussion or lab twice a week.
- NOT BE AT 8:30AM, USE A SMALLER ROOM -- helps w/ engagement
- I think he is a stellar lecturer and keeps the pace good answering questions, however, the slide decks are extremely scattered and confusing. 30 seconds of spacing out and you need to wait for the next slide to understand what is going on because the order is confusing. It also makes it difficult to look back on the slides when doing problem sets for insights. I would recommend making the decks with better titling and more consistent with chronological order of how he goes through the. Basically, making the slide decks both readable and presentable (because they are very presentable and does a great job of it).
- The class felt a little fast, especially when discussing mathematical derivations which many people have a tough time following. I think it would be best to cover less content so that it can be taught more slowly, making sure that less people get lost along the way.
- N/A
- I think it was too math/statistics heavy. Yes, it's important to know what a correlation coefficient really means about how X explains the variance in Y, but rewriting the equation 4 times in between isn't especially helpful for me. I think these derivations make intuition about the underlying math harder, rather than easier, by distracting from principles that could be boiled down in an even simpler way. Personally I found it difficult to follow the math, and found it to be a distraction compared to pictures of graphs representing the regression outcomes themselves. I don't know whether the math was actually too difficult to follow, I just didn't have the attention early in the morning to follow it. Perhaps in the afternoon it would be worthwhile.
- Smaller class and less inclusive to seniors.
- Lectures were long and repetitive. Cold calling was funny.
- I think it would be useful to relate more complex concepts to 104 briefly just to quickly remind the class about the foundations
- I believe lectures were sometimes too fast. Maybe, slowing down or giving supplementary videos beforehand could be ideal so that I could have understood class better.
- Reduce the number of topics. Felt like we were rushing through them
- More in-class quizzes (not necessarily for a grade) just so it isn't as much straight lecturing
- This course is way too hard. the teacher is very strict and knows the content very well, but I was always confused in class.
- I think more time could be spent practicing with some topics. The course felt very fast and overwhelming oftentimes. Would have liked maybe even another lecture to nail in some key concepts.
- If the notes were the exact same as in-class lectures, then it may be easier to follow along after classes.
- I think unfortunately there is a lot of material to cover in this course, which results in certain aspects being covered very quickly in order to start the next idea. In class, I found it extremely difficult to take notes due to the pace of the class, which would sometimes result in me zoning out if I got behind. I also think some more hints on the problem sets with how to approach problems would be great, as it can often be hard to get all your questions answered at office hours. Lastly, while I do understand the point of the pop quizzes in the sense that they track your attendance and make sure you are paying attention, I think they are somewhat unfairly weighted for how difficult they can be in the moment, as they have been the main force dragging down my grade despite my straight attendance.
- Different participation grading - random quizzes to measure attendance were not fair and often times discouraging - attending most of the classes might still get low participation grade if you missed on days there were quizzes
- I would change the format of the midterm a bit. It was a lot of information to process in a short amount of time, and the open-book format was unfamiliar. I would make it more of a traditional exam.
- I would make the HW less theoretical and more practical
- I would prefer more problems similar to the ones asked on the midterm. Since we were not allowed Stata on the test, the nature of several questions was different than that of the problem sets, so I would have appreciated additional practice midterms and problems in preparation for the midterm/final.
- N/A.
- There should be a better way to take attendance given we only had 7 quizzes. Would encourage have an attendance component as well.
- I would consider maybe a slower-paced course. It is incredibly hard to keep up with the quick explanations and the classes aren't recorded (slides are made available). The quizzes and their distributions throughout the semester aren't fair at all either - they are given at random times and some are worth way more than others. People who were at Professor Thomas's class throughout the whole semester might've missed a quiz or two (which really plummets your grade) while others that are rarely there might've gotten full credits. Finally, the midterm is way too long. Not knowing what the curve will be like right after the midterm really makes people desperate.
- - smaller problem sets - recording lectures (slides don't do justice to material) --> hard to remember class discussions from august in december - easier in class quizes
- Potentially a slower pace in lectures so notes can be taken while you are ingesting what the teacher is saying. I know its alot of content, but some of intution could be built less with mathematical proofs on the board and a better explanation of whats actually going on.
- I sometimes thought that the lectures went a bit too fast for me which could be more of a personal challenge, but overall great learning environment.
- Problem sets are far too long - they are extremely helpful in terms of learning but just far too long. The professor is an amazing person who clearly cares a great deal about the students. But the lectures just go far too fast. I feel like we spend too little time on the content during lectures and too much time on questions from a handful of students. If we redistributed the time in lectures - going slowly over the content and reserving office hours as the time for questions - people would probably grasp on to the content much more. And there wouldn't be as many questions during the lectures in the first place.
- Can the lectures be recorded? I believe that attendance is already taken through pop quizzes/attendance sheets, but I would greatly appreciate lecture recordings because they do move quite fast and I would love to be able to replay a moment I don't understand when reviewing content for exams.
- 1. No 8:30 class time (very difficult to maximize contributions when that tired). It's my responsibility as a student to adjust my sleep schedule; however, in the reality of college, there are going to be late nights of work, and those make it hard to get a lot of sleep the night before class. 2. Provide 1 - 2 review class lectures. I know that we have office hours and pset solutions available to check previous topics, but it's difficult to balance that with learning the new topics. A review lecture every 6 weeks would really help bolster my understand of topics and fill any gaps. 3. Make the midterm shorter; I don't know any one who finished question three because we all ran out of time. Seemed unfair.
- Nothing
- this course should never be taught at 8:30 am, far too much content to digest
- Maybe make a problem set due every week, force the habit of sitting down consistently and getting it done. I might gently recommend that Thomas is reminded that most students are here to learn. I think how he answered a few questions did not come across as kind.
- I would rethink the pop quiz nature component of the class. I think there are better ways to have 1 or 2 random absences in classes with quizzes not impact a student's grade. I would consider letting students drop their lowest which can even be conditional on collecting general attendance and them attending at least x% of classes.
- Move slower. At times I could not keep up and was very quickly behind.
- A Slower pace to the course may be beneficial. Coming into the semester it was assumed we remembered everything from Econ 104
- The course policies heavily punished those who were sick or had unavoidable unfortunate circumstances. Professor Duncan's policy of not accepting STINFs under any circumstances meant that he would give you a 0 on the pop quizzes if you were extremely ill or incapacitated for any other reason. Additionally, even for being 3 minutes late, he would give you a 0. In addition, the weighting of the quizzes meant that being sick or late by 3 minutes one time would decrease your grade by 3.25% percentage points. Two days of illness would mean that even with a 100 on the final, it would be impossible to get an A. The course is structured to be unaccommodating and punishes people heavily for things completely outside of their control as opposed to their knowledge or effort in the class.
- The lengths of each problem sets were at times inconsistent, which made scheduling time for it challenging. Even with (generally) the same number of questions, a 15-part question can take longer than a 10-part one, except for when the 10-part question requires large amounts of work per section and each piece of the 15-parter is more straightforward. Discussion sections were generally used well, but I would like to see PSET review components shortened to a few key sections of each question that a lot of students missed, with the rest of the time set aside for actual content practice and review. These are all small things, though, that didn't really impede a positive learning environment.
- Do not have at 8:30 am (uncontrollable for this year however, the professor was extremely critical of those who would come in late), and the professor specifically goes through portions of the lecture too quickly to comprehend so that students are forced to go through notes on their own time. While this was effective to motivate students to learn on their own time, it would have been more useful to have both in-class time as a valuable resource. While lectures were entertaining, I taught myself the entire class.
- The pop quizzes add a lot of unneeded stress to the class - maybe have planned quizzes and/or alternative incentive for class attendance

- The material was very difficult. Super-duper useful (especially since I'm also a sociology major so knowing how to interpret and use empirical data to solve real-world issues is super important), super helpful in terms of what research I want to do in the future, but also just generally not an easy course.
- Solid materials
- So much interaction, so many opportunities to ask questions, and so many opportunities to show you're working hard. Dedicating time to this class always feels like it's worth it.
- This class was incredibly stimulating thanks to Professor Thomas's unique ability to connect econometric concepts to the relevant literature and his own research - he brought the material to life in an accessible and engaging way. His focus on building intuition set the course apart, helping us understand the "why" behind the methods rather than just the mechanics. It was a perfect balance of depth and clarity that made every lecture thought-provoking and rewarding.
- This class was super engaging, even at 8:30, Prod Thomas always captured everyone's attention. It was also super applicable to the real world, and pretty much all of the in-class and problem-set questions were based on real-world data.
- Content, professor was also very engaging
- The slides were clear
- The content and applications in real world were compelling.
- The problem sets made it that you applied the things you learned to real world issues and so it made it very relevant. Also like you have to think really hard about all the concepts
- This class provided me with a clear understanding of the tradeoffs that economists need to make in building econometric models. It built for me the confidence to deal with complicated datasets in my future research.
- It was a very challenging class
- Used what we learned on real world statistical examples, and found out how many papers use bad stats
- it was hard
- Although it is a very quantitative course, the professor emphasizes on thinking intuitively, which improves critical thinking and makes the class intellectually stimulating.
- N/A
- I think we could use more example variety to help understand the material in the real world.
- The class goes on too fast
- The lines of math at the beginning of the course were very hard to follow in a lecture format and it was not immediately clear why they were relevant. It might have been helpful to have a chart or sheet showing the different estimation methods that we were deriving.
- The material was challenging but rewarding
- More correlation between class and psets as psets were mainly in R
- Professor made this more stimulating than it should have been material wise.
- The material itself was very stimulating and really drove interest for myself and many others.
- The content makes this class interesting.
- Taught the complexities and ambiguities of econometrics principles that set a good understanding for real world application.
- i loved the problem sets! they're very different every time and are very applied, they're also biweekly so you have enough time to think and discuss with friends. i think the way duncan pushes his students to do better and analyze things at a deeper level really was transformative for me
- You directly apply the things you learn in problems/what you see in the news.
- The problem sets do a good job of reinforcing the material learned.
- I really liked the pop-quizzes and the problem sets being bi-weekly. I feel like whether it was going over the class notes or working on the problem set, I felt like I was working for this class even a little bit every single day which actually helped me to stay up to date with the work and keep using all of the new content.
- have smaller problem sets due every week. or an example problem to do after each lecture.
- In-depth econometric analysis, real-world example that brought color to learning. Think the course would be conducive to a final paper/investigation rather than final exam.
- Very intellectually stimulating, I very much liked how everything was tied to real-world applications.
- The professor's teaching style and manner of keeping students' engaged.
- Material was quite boring, professor was good at lecturing. Made the material more interesting with good examples and problems.
- N/A
- I thought econometrics would be boring and stats-heavy, but it turned out that this course taught really interesting concepts related to how variables are represented in models. Learning and practicing interpreting estimates from different kinds of regressions, and learning economic experimental design and hypothesis testing was genuinely really fun, because its just interesting the kinds of ways we can represent such relationships. The professor and the TAs did an excellent job conveying these core ideas, and restating and iterating on them throughout the class, and I found that engaging. The homework was a little bit Stata/math heavy in my opinion, but the questions related to economic intuition or statistical intuition or experimental design were genuinely fun to answer
- This class was super stimulating because the professor tried his best to engage everyone and develop the intuition for data analysis.
- I really enjoyed the lectures, even though they were at 8:30. The cold calling really made me understand the material better and look at it through the lens of other students. Office hours were always fun and it was a pleasure to interact with Duncan.
- Duncan.
- it felt like more of a discussion than a lecture at some points which was stimulating
- I believe the class was extremely stimulating because every day I had to bring on my full attention to class.
- Real-world examples in the problem sets
- we used real data to tackle some of the examples in class. very helpful
- I liked the ability to apply it broadly to a variety of real-world problems.
- It was very intellectually stimulating.