KA
16 дек. 2017 г.
Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.
DA
10 мар. 2019 г.
This module was the maximum. I learned how powerful the use of Regression Models techniques in Data Science analysis is. I thank Professor Brian Caffo for sharing his knowledge with us. Thank you!
автор: Aida B S H
•21 апр. 2021 г.
Regression analysis has been a very insteresting course. I've learned a lot, and was happy to do my graphs and analysis in R!
автор: Damien C
•6 дек. 2016 г.
Great ressources. Usefull presentations, maybe too rich for a newbie.
It was too fast for me. Could be done in 2x more time :/
автор: Richard F
•17 июня 2017 г.
This is the most challenging course so far - new concepts, new approaches and application to a wide variety of situations.
автор: Connor B
•12 сент. 2019 г.
Learned a lot and enjoyed the course project. Would like to have two course projects because I gain the most out of them.
автор: Carlos B
•20 июня 2017 г.
Thank you for the chance to review all the fundamental and applied mathematical and statistical aspects of data analysis.
автор: Stefan S
•4 мар. 2016 г.
Not the easiest course, but very rewarding if you hang in there. The material is very well explained with ample examples.
автор: Nino P
•24 мая 2019 г.
Similarly to statistical inference, this is a bit harder course in the specialization. Still passable and recommendable.
автор: German R M S
•7 июня 2018 г.
Excelente curso, requiere de esfuerzo y dedicación, ademas de una solida base estadística. Práctico y de mucha utilidad.
автор: Vitor P B
•25 окт. 2020 г.
Very detailed and complete course with heavy theorical concepts which are all very useful for data science applications
автор: Daniel A S
•10 июня 2020 г.
Very good and complete, the professor is very clear in his explanations and very helpful for data science applications.
автор: Georgeanne P
•31 мая 2021 г.
This is a tough course. I needed to use materials outside of the course to get the full understanding. But is it good.
автор: Ekaterina S
•12 мая 2019 г.
It was a very usefull course. It is a very good approach to the theme - the main essence without much math difficulty.
автор: Ivana L
•30 янв. 2016 г.
One of the most valuable course in series. Also one of the hardest, expecially if you are newbie to regression models.
автор: Marco B
•21 дек. 2017 г.
very useful! it provides both theoretical framework and practical skills!
it helped me improve my daily data analysis!
автор: weiting L
•27 окт. 2016 г.
nice and practical class! I think if provide some recommend reading may create more deeper insight in regression
автор: Joseph R
•3 мар. 2016 г.
A very well organized course with nice simple explanations and introductions into the world of regression models
автор: Gregorio A A P
•26 авг. 2017 г.
Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.
автор: marcelo G
•14 авг. 2016 г.
Outstanding material with different levels of difficulty and depth on the subject. Great source material.
автор: Greg A
•22 февр. 2018 г.
I thought I understood regression, but this course help me gain new insights and really sharpen my skills
автор: Nilrey J D C
•29 окт. 2017 г.
Very concise and informative. This gives me a good review in my college statistics regression subjects
;)
автор: Erika G
•27 июня 2016 г.
I had a lot of fun in this course. The exercises in the text and quizzes help me understand the concepts
автор: Hewan D
•4 мар. 2021 г.
I am so happy taking this course. This will open loads of doors for my data analysis. Thank you so much.
автор: Carlos M
•11 июля 2017 г.
I learned a lot of theory and practical applications of residuals. The swirl assignments were great too!
автор: Robert W S
•21 нояб. 2016 г.
Excellent course. Might be difficult to get full value of information without prior exposure/background.
автор: André C L
•13 дек. 2018 г.
very good practical approach, with good theoretical coverage of most important principles of regression