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Modern Regression Analysis in R(으)로 돌아가기

콜로라도 대학교 볼더 캠퍼스의 Modern Regression Analysis in R 학습자 리뷰 및 피드백

강좌 소개

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 https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from photo by Vincent Ledvina on Unsplash...
필터링 기준:

Modern Regression Analysis in R의 2개 리뷰 중 1~2

교육 기관: Michael B

2021년 8월 16일

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.

교육 기관: Najib B

2021년 10월 1일

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.