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존스홉킨스대학교의 통계적 추론 학습자 리뷰 및 피드백

4.2
별점
4,346개의 평가
879개의 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 847개 리뷰 중 651~675

교육 기관: Sudha S S

2016년 4월 28일

Teaching material is very good. But I feel the Professor's explanation is monotonic and uses more of textual definitions rather than simple explanations which are required for starters.

교육 기관: Lucas L A A S

2016년 6월 8일

The course is really interesting, but I believe the professor approach to describe and explain the topics is really confusing. I had to search other resources to clarify the topics.

교육 기관: Pritesh S

2018년 12월 14일

A pretty tough course, but I learned some new things. The assignments can be be made better, as well as the evaluation of assignment, which is being done by peer review right now.

교육 기관: Bjoern W S

2016년 3월 14일

very difficult with lots of math not properly explained. What's the point of learned all these formulas by heart if you cannot use the properly because that is not explained well.

교육 기관: Josh J

2017년 5월 1일

Material was interesting. Did not enjoy the teaching method of Prof. Caffo. Very scripted and skips way too fast through some of the equations and R code he's trying to teach.

교육 기관: Ramy H

2017년 10월 1일

Material should be supported by more examples. ie. at the end of the course, I couldn't perform a basic statistical test.

Bootstrapping modules completely missed the context.

교육 기관: César A C

2017년 11월 16일

You will review basics and main statistical theories. However the course videos and explanations are not as intuitive as in the previous courses. Statistic is always tough.

교육 기관: Svetoslav A

2016년 12월 19일

3.5 - Good, but I feel some of the explanations were over complicated a little compared to other coursers such as openintro to stats. Overall good experience though

교육 기관: Hongzhi Z

2017년 11월 16일

整个专题里面boring的一门课之一,Brian教授的视频一直是1.25time速度看完,有些例子例如最后的Hypothesis testing 真的学得很困难,即使我在大学时候曾经上了概率统计的课,对没有数学和统计基础但想从事数据科学的人员真的是十分不友好,希望改进:1、课程视频变得有趣 2、PPT资料里面的公式详细解析

교육 기관: Stefan P

2016년 1월 30일

Brian Caffo is a brilliant mind. I am sure, but in a way for me it is difficult to follow. In parallel I checked out Khan Academy and it was easier to understand.

교육 기관: Fabien N

2019년 11월 15일

I find the lectures sometimes not clear enough to answer the quizzes questions. On the other hand, the course provides material in many ways, which is very nice.

교육 기관: Asier

2016년 3월 10일

At times the content can be confusing. Some points are clearly explained. "Data Analysys Tools" course is a good complement in order to understand the subject.

교육 기관: Talant R

2016년 8월 26일

Covers a lot of info too fast! Some concepts are not clearly explained , had to surf online to get better understanding. Overall, fine course, very practical.

교육 기관: Yadder A

2018년 1월 25일

I didn't like the way how the professor explained the topics. It was difficult to understand him. I just understood when I did the swirl activities.

교육 기관: Diego T B

2017년 12월 4일

Very useful but too many concepts. It was hard to follow him during 20 minutes. Videos are very extensive, also useful. But take into account this.

교육 기관: dhaval s

2017년 2월 21일

Indept videos and materials should be provided for this course. The lectures are not enough to understand the Statistics involved in data science.

교육 기관: Chouaib N

2019년 11월 11일

The course content is very interesting and sums up fundamental aspects of statistical inference. But the way the course is presented is average.

교육 기관: Aaron S

2018년 5월 7일

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ts just to have a chance of passing this one.

교육 기관: Mohammed A E M

2017년 7월 17일

the subject kinda not hard but not easy to understand also, how ever the instractor was kinda fast which made me lake some of the information.

교육 기관: Ivan G

2017년 1월 7일

To be honest, I like the subject but found the course material and content not very well structured. I missed more mathematical foundation.

교육 기관: Pawel D

2016년 12월 3일

Brian Caffo is explaining the Statistical Inference methodically, but he could work on making the lectures less tiresome and monotonous.

교육 기관: Ramon S

2017년 5월 19일

Not really a logical path to follow. Too much topics for me. I really needed more examples with code.

Thanks a lot for the lessons!

교육 기관: Naeem K

2016년 8월 8일

The amount of materials is more than course period. You may need to study a couple of other resources to understand the course.

교육 기관: Hernan S

2016년 4월 15일

The subject is interesting, but the explanations are a little confusing. May need more diverse real-life examples to relate.

교육 기관: Masahiro H

2016년 3월 27일

it gives an idea of how one is prepared to ingress to Data Science. I

see that I need to review it more carefully later on.