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존스홉킨스대학교의 통계적 추론 학습자 리뷰 및 피드백

4.2
별점
4,261개의 평가
860개의 리뷰

강좌 소개

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data....

최상위 리뷰

JA
2018년 10월 25일

Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .

MI
2020년 9월 24일

the teachers were awesome in this course. I liked this course a lot.Understood it properly.Thanks to all the beloved teachers and mentors who toiled hard to make these course easy to handle.Gracious!

필터링 기준:

통계적 추론의 829개 리뷰 중 476~500

교육 기관: Aashay M

2016년 2월 25일

This is course is well written , the Lecturer notes are very handy and Swirl Lessons give us Hands on Experience in Practical Implementation.

Thanks for the instructors

교육 기관: Rodrigo A d S R

2018년 8월 20일

Really good course, a bit difficult since it jumps right into technical language, but it gives you a good solid base for the following courses in the specialization

교육 기관: Vitalii S

2017년 7월 4일

I think it would be better to send solution in .html and not .pdf, because you need to install 3rd party software. In other aspects course is very cool. Thank you.

교육 기관: Liam P B

2020년 6월 1일

Good introduction to probability and statistics. I think it moves too quickly for absolute beginners but its probably a fine compromise between depth and breadth.

교육 기관: Jordan G

2016년 2월 14일

I wish there was more R programming focus. I feel like there was a lot of theory, and then a blanket "t.test will cover this" treatment of implementation in R.

교육 기관: Piotr K

2016년 10월 23일

Sometimes videos was difficult to understand. I needed to watch most of lectures twice. On other hand it was worth doing and I've learned basic statistics.

교육 기관: Connor G

2017년 8월 22일

I learned a lot from the lectures and felt that the quizzes were adequately challenging, but I was expecting to do more with the peer-graded assignments.

교육 기관: Max M

2017년 10월 31일

Maybe a little fast paced for someone seeing these topics for the first time, but overall great content that I think will be a great help in my career.

교육 기관: Veronica

2018년 11월 4일

I've tried to learn statistics for so many time and it is never less painful. This course is a good overview and exercises/quiz always help the most!

교육 기관: David J G

2016년 2월 4일

I think you can get a lot from this course, but you have to deploy a reasonable amount of time to find for yourself more in depth concepts elsewhere

교육 기관: Antonio F

2016년 6월 25일

It is a good course, well taught. A full comprehension of the subjects however needs more work and research than what is needed to pass the course.

교육 기관: Nik M N N G

2019년 3월 27일

Overall, this is a good course to learn statistics. The quality of the video could have been better but the stuff presented is still clear to me.

교육 기관: Tommy S

2019년 3월 8일

I really enjoyed the course and material. Very good explanations in the video and the book does a good job of explaining what the videos go over.

교육 기관: Rahul V

2021년 7월 25일

A​ssignments helped me to have a solid intuition of core concepts in statistics. This was a good start to the machine learning series. Thank you

교육 기관: Jay S

2016년 7월 29일

A foundation course for data scientists! Basic statistics from University of Amsterdam on Coursera would be nice pre-requisite to this one !

교육 기관: Ramiro A

2016년 6월 28일

Content was Great, difficult to understand some times. I had to review more sources to get the clearer idea.

Totally enjoyed the challenge.

교육 기관: Robert W S

2016년 3월 17일

Good refresher course. It'd be a little steep of a learning curve for someone new to hypothesis testing/confidence intervals in four weeks.

교육 기관: Connor B

2019년 8월 28일

The course project was the most beneficial for me because I got to work with real data it helped me understand the concepts much better.

교육 기관: Vincent G

2017년 8월 14일

Very good material. I only wish the examples could be more varied to include some "business" examples as opposed to mainly bio med ones.

교육 기관: Juan B M V

2016년 9월 24일

Touches all the key concepts of statisticas inference. A bit challenging, even more if you don't have previous knowledge of statistics.

교육 기관: Harsh G

2020년 5월 29일

Overall a great course to learn and understand, few concepts weren't explained properly and I faced difficulties in adapting to those.

교육 기관: Scipione S

2020년 6월 16일

Nice Course, probably it needs more time to study in deep certain topics like tests, confidence intervals, and resampling techniques.

교육 기관: Enrico D

2017년 4월 24일

It is good but you have to study by yourself using different material as the video contents are not enough to understand the subject

교육 기관: Tomas A M

2020년 3월 25일

Course lectures could be a bit simpler. without that many theoretical demonstrations & more pragmatics summaries of the concepts.

교육 기관: Joost L

2020년 10월 18일

More difficult than the previous modules. Some explanations by the teacher seem to expect some basic knowledge on statistics.