Introduction to Computational Statistics with R
Lecture, three hours; discussion, one hour. Requisites: course 20, Mathematics 33A, and one course from course 10, 12, 13, Economics 11, 41, or Psychology 100A, or score of 4 or higher on Advanced Placement Statistics Examination. Introduction to computational statistics through numerical methods and computationally intensive methods for statistical problems. Topics include statistical graphics, root finding, simulation, randomization testing, and bootstrapping. Covers intermediate to advanced programming with R. P/NP or letter grading.
Review Summary
- Clarity
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10.0 / 10
- Organization
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10.0 / 10
- Time
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10-15 hrs/week
- Overall
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10.0 / 10
Reviews
Well designed course. Getting an A is easy as long as you do the work
Miles Chen is the best professor in the Statistics Department. His presentation are clear and succinct, he usually post lectures on his Youtube which is helpful for reviewing his slides after class. The homeworks are fairly difficult, and are more so time consuming than impossibly challenging. In-person exams, and this is my first time doing these for a programming course. The exams were easily the most challenging aspect but Professor Chen has a courteous grading policy. He will curve grades if they are low. His primary concern in teaching this course is that you learn something valuable for your future endeavors. He does not want you to stress about grades. Watch the lectures, spend time on the homework, and you will do fine.
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Course
Grading Information
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No group projects
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Attendance required
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1 midterm
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Finals week final
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100% recommend the textbook
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