PUB AFF 60

Using Data to Learn about Society: Introduction to Empirical Research and Statistics

Description: Lecture, three hours; discussion, two hours. Introduction to statistics through examination of topics of public interest. Familiarization with research design principles and hands-on data analysis using statistical software. Students learn how to find and organize quantitative data; summarize, display, and interpret data; draw inferences from samples (including understanding margins of error, standard errors, and confidence intervals); test hypotheses about associations between two variables (including tests of proportion, t-tests, chi-squared, correlation); and communicate findings to lay audience. Letter grading.

Units: 5.0
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Overall Rating 4.7
Easiness 3.7/ 5
Clarity 4.3/ 5
Workload 4.0/ 5
Helpfulness 4.3/ 5
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Overall Rating N/A
Easiness N/A/ 5
Clarity N/A/ 5
Workload N/A/ 5
Helpfulness N/A/ 5
Overall Rating N/A
Easiness N/A/ 5
Clarity N/A/ 5
Workload N/A/ 5
Helpfulness N/A/ 5
Overall Rating 4.5
Easiness 3.5/ 5
Clarity 4.5/ 5
Workload 4.3/ 5
Helpfulness 4.8/ 5
Most Helpful Review
Winter 2024 - YOU NEED TO TAKE PA60 WITH PROFESSOR LOYA!!! He is hands-down one of the most caring and dedicated professors I have had at UCLA. He truly cares about his work and takes the time to get to know as many students as possible. While this class was not the easiest, it's definitely tolerable with the help of Professor Loya and the TAs, as well as the forgiving nature of the class. Both lecture and discussion were mandatory, and he randomly took attendance 3 times throughout the quarter. He also uses lecture slides that correspond with the textbook material. With that said, you do not need to buy the textbook for this class unless you want to use it to supplement your studying. Professor Loya made lecture bearable and was super funny. I took AP Stats, so I knew most of the material, but it's much different since everything you do is done by hand without the help of an advanced calculator (only basic calculators are allowed on tests, not TI-84s). Learning to code in R definitely has a steep learning curve, but Loya posts tutorials for the first few labs, and the TAs are instrumental in the process. I had Hannah King as my TA, and she was amazing. She was amazing at responding right away to questions and helping with troubleshooting when needed. The exams are open-cheat sheet (one 8.5x11 sheet of paper, front and back) and he tells you most of the material that's going to be on the exam beforehand. I definitely recommend going over all of the content covered on the slides even if he doesn't mention it - there were a few curveball questions I wouldn't have known on exams if I didn't go over everything. I crammed all of the homework problems and information onto a sheet and was good to go. This class is not the easiest, but super manageable as long as you use the resources Professor Loya and the TAs give to you! Best of luck!
Overall Rating 4.8
Easiness 3.6/ 5
Clarity 4.7/ 5
Workload 3.5/ 5
Helpfulness 4.9/ 5
Most Helpful Review
Fall 2020 - Professor Phillips is a gem! Her class was fun and informative and would recommend 10/10! Class Overview: Grading consisted of two problem sets (25% total), a midterm exam (25%), take home final (25%), two mini exercises (15% total), and various other little assignments that were graded for participation (10%). Not too bad and she did offer various opportunities for extra credit. As far as for course content, it is largely a review of an intro stats class (STATS 10 or AP Stats), but you will also learn about how to code with R. Lectures: Lectures were live (although she did record them). Personally, I found going to live lecture was better as sometimes it can be hard to follow along without knowing the context (i.e. what question a student asked). She was funny in lecture but was still able to stay on track. Her lectures were also example based which was helpful imo. Labs: Each week for lab would consist of reviewing the lecture and working on either the mini exercise or problem set for the particular week. They did usually take the full two hours but it was nice to be able to get much of the work done in lab and ask any questions in the process. Overall, the TAs were very knowledgeable and helpful both in lab and on the discussion forum so no problems there. Problem Sets/HW: The assignments were all on R. The instructions were pretty clear and the TAs did post a good amount of resources to help with coding. There was plenty of time to do the assignments, but they did have many parts and subparts to each question so be aware of that. Exams: The midterm was as basic exam on CCLE (open note) that consisted of M/C, short answer, long answer, and an extra credit. Average was in the 90s so not too difficult. The final is a take home exam on R (basically a condensed version of a problem set). Reading: There were reading assignments for each class (and sometimes a podcast). They weren't really necessary and I didn't read them beyond a quick skim before each lecture. Clarity/Helpfulness: Professor Phillips and the TAs were all helpful, especially considering the virtual quarter. They were active in the discussion board, helpful in OH, and overall very accommodating and flexible. Overall: TAKE THIS CLASS! You will definitely learn a lot (esp about R) but its not overwhelming and she is very helpful and funny!
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