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Avis et commentaires pour d'étudiants pour Inférence statistique par Université Johns-Hopkins

4.2
étoiles
4,053 évaluations
805 avis

À propos du cours

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....

Meilleurs avis

JA

Oct 26, 2018

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

Sep 25, 2020

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!

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576 - 600 sur 773 Avis pour Inférence statistique

par Richard M A

Nov 28, 2016

Nicely outlined and broad in scope, but Brian's presentation is kind of dry. It often appears that he is reading off a script, and sometimes his emphasis on technical details takes away from ease of understanding.

par Fernando M

Mar 02, 2016

I think the theory is too dense, but with a weak link with R. I understood better with swirl than with the videos. I'd suggest a more organized video with less draws and annotations. They confused me sometimes.

par Suman G

Mar 31, 2018

Statistics & Probability being two of the toughest subjects, this course could have been taught a bit more novice friendly way, so that learners with no background in maths can also grab the lectures easily

par Fernando L B d M

Sep 29, 2017

I had some difficult to follow the lessons, because the professor is kind of reading the material and not building the concepts during class time. I had to look for other videos and texts out of coursera.

par Abhinav G

Feb 11, 2016

As someone who isn't from math background many of concepts thought in here weren't quiet clear or intuitive. Could use more details or pointers to reading materials to help understand the concepts better

par Paramesh S

Jun 05, 2020

Disappointed with the way the course has been taught. The instructor just reads out from the slides. Had to refer lot of other material to understand the topics being taught in this course.

par SUDIPTO M

Dec 12, 2017

i belive this course should be taught in 6 weeks at least and not 4 . There are multiple areas which needa deep dive. with the month based subscription it is very difficult to deep dive

par Sudha S S

Apr 28, 2016

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.

par Lucas L A A S

Jun 08, 2016

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.

par Pritesh S

Dec 14, 2018

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.

par Bjoern W S

Mar 14, 2016

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.

par Josh J

May 01, 2017

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.

par Ramy H

Oct 01, 2017

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.

par César A C

Nov 16, 2017

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.

par Svetoslav A

Dec 19, 2016

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

par Hongzhi Z

Nov 16, 2017

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

par Stefan P

Jan 30, 2016

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.

par Fabien N

Nov 15, 2019

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.

par Asier

Mar 11, 2016

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.

par Talant R

Aug 27, 2016

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.

par Yadder A

Jan 25, 2018

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.

par Diego T B

Dec 04, 2017

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.

par dhaval s

Feb 21, 2017

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

par Chouaib N

Nov 11, 2019

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

par Aaron S

May 07, 2018

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ts just to have a chance of passing this one.