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学生对 约翰霍普金斯大学 提供的 统计推断 的评价和反馈

4.2
4,212 个评分
852 条评论

课程概述

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....

热门审阅

JA
Oct 25, 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 24, 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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776 - 统计推断 的 800 个评论(共 819 个)

创建者 Liew W P

Aug 23, 2016

Personally, I feel that the way of sharing and teaching was assuming everyone is an expert in this subject. This course need to be reviewed to make it more suitable to various groups of profession as not everyone has the same level of mathematics background.

创建者 Jeffrey G

Aug 16, 2017

In general, I'm really excited about statistics, there are so many interesting and cool problems to work on, and yet, here I am, forced to do an analysis of, "The Effect of Vitamin C on Tooth Growth in Guinea Pigs."I can't make this shit up...

创建者 Deas R

Feb 15, 2016

Seeking out supplemental material is not only helpful, but necessary. This course does not provide a foundation of knowledge for inferential statistics so much as present several equations and functions and describe how one might use them.

创建者 Sharon E

Jul 21, 2020

This course starts with the assumption that you understand all of the terminology covered and that you already have a thorough understanding of statistics and inferences. I'm sorry - if I knew all that I wouldn't be taking this module.

创建者 Paul K

Mar 28, 2017

Poor quality audio. Monotonous lecture style with frequent inaccuracies in delivery (says one thing but actually means another). I found my motivation and performance dropped sharply in contrast to prior lectures in this series.

创建者 raunak r

Dec 25, 2016

Very disappointing!!!!!!!too much emphasis on mathematical notations....where are the practical applications?lack of examples....it seemed more of a prose than a lecture....would not recommend to a beginner.Period

创建者 Fabiano C

Feb 5, 2017

So far this is the poorest course in DS specialiation. Coins and dices all the time, Brian reads to the camera. It is just like reading a book, a very boring one. Examples from real life could boost interest.

创建者 Marco A M A

Apr 7, 2016

poor course, saturated, with an instructer that uses big words and does not explain many difficult ideas, and take for granted that the leaner knows a lot of probability and statistics.

创建者 Evgeny P

Oct 24, 2017

Course materials are not balanced, it is not enough information to follow conclusions. Course gives set of tools but doesn't build solid foundation and intuition about how to use them.

创建者 vaibhav p

Sep 10, 2017

Quality of teaching needs to improve. The professor needs to be more enthusiastic when giving the lecture.

The course content should involve more examples to help cement the concepts.

创建者 Adnan B

Jul 19, 2019

Not a good instructor or course material

it felt like if he was trying to teach to phd candidates

I just went to Khans academy for every topic.. didnt learny anything from him..

创建者 Rennê L C V

Oct 13, 2017

The teatcher know so much about the topic that he can't put himself on students shoes and see that his classes are really hard to understand. Also, the audio was pretty bad.

创建者 Sergey Z

Jun 9, 2016

The worst course I've ever taken.

Bad sound quality, dead discussion forums, not possible to understand material without external (not mentioned in the course) sources.

创建者 Farhad S

Apr 19, 2016

This course is very difficult to follow, not because the topics are hard or too technical but mostly due to lecturer's poor job in explaining and creating a narrative.

创建者 Martin L

Jul 8, 2017

It's a very interesting topic but I had to rely on a text book to understand it! I struggled to understand the lectures and reconcile it back to the quizes.

创建者 Maria

Dec 9, 2017

The teacher does not explain clearly the concepts. I will not recommend this course to somebody interested in the subject as it is not effective to learn.

创建者 Jeff B

Mar 31, 2018

The lecturer is very difficult to follow. His teaching style is very hard if you don't already have a background in statistics. Sorry but true.

创建者 Heather D

Mar 14, 2018

Basics of statistics are not covered. Teacher jumped into more advanced material. I must use many outside resources to actually learn this.

创建者 Abdelrahman S H

Jul 3, 2017

The content of this is mainly theoretical, and the practical part is so small compared to other courses in the same specialization.

创建者 Grigory S

Feb 28, 2018

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创建者 Neeraj K

Apr 7, 2018

Very bad teacher. He seems in a hurry. Not explaining anything clearly.

Through out the idiot wasting time and money

创建者 Guan C

Jul 4, 2017

Didn't explain things clearly, the companion book uses many inconsistent mathematical symbols which confuses me.

创建者 Imogen S

Oct 31, 2017

Not a very well-structured subject. Need to make clearer demonstrations and explanations on the theories.

创建者 sateesh

May 3, 2016

The course is very difficult to comprehend..Moreover the examplanations given ar not concise and brief..

创建者 Ravi T B

May 7, 2017

No proper meaningful explanation for the logic derived, especially in Probability, the core of stats.