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Comentários e feedback de alunos de Modern Regression Analysis in R da instituição Universidade do Colorado em Boulder

11 classificações
4 avaliações

Sobre o curso

This course will provide a set of foundational statistical modeling tools for data science. In particular, students will be introduced to methods, theory, and applications of linear statistical models, covering the topics of parameter estimation, residual diagnostics, goodness of fit, and various strategies for variable selection and model comparison. Attention will also be given to the misuse of statistical models and ethical implications of such misuse. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at Logo adapted from photo by Vincent Ledvina on Unsplash...
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1 — 4 de 4 Avaliações para o Modern Regression Analysis in R

por Michael B

16 de ago de 2021

Thorough review of simple linear regression and multiple linear regression with a good bit of well-explained theory and challenging assignments. Highly recommended for those getting their feet wet in regression and for those already familiar with the techniques but need to brush up on the theoretical aspects of it. One of the better courses on Coursera.

por Najib B

1 de out de 2021

This course is the best out there for those who want to learn R for regression and the theoretical foundation of regression. Professor Zaharatos explains the meth background needed in a excellent way. My knoweldge of math limited yet I was able to pass most of the assignments. The assignments are very well thought. Some minor problems with the autograded assignments but most of them are manageable after sometime. I highly recommend that course for everyone who making at their mid-way to statistics.

por Steve W

13 de fev de 2022

Content and intent is great. The autograder for assignments is frustrating.

por David S

12 de abr de 2022

Peer reviews appear to be unreliably completable. After performing all the work I have not found any way to get 2 of 6 peer reviews completed so I could complete the course. I am providing 1 star because the lack of ability to receive credit for valid work seems to be "table stakes". It is a minimum bar of performance. Further, this course is a valuable component in the Boulder masters program. For a ~ $20K it seems that Boulder may be exploiting students.