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통계적 추론(으)로 돌아가기

존스홉킨스대학교의 통계적 추론 학습자 리뷰 및 피드백

4.2
별점
3,844개의 평가
767개의 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

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 .

AP

Mar 22, 2017

The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.

필터링 기준:

통계적 추론의 734개 리뷰 중 576~600

교육 기관: Joe F

Nov 27, 2016

Materials need to be updated - there are way too many inconsistencies between videos, exercises, and slides.

교육 기관: Vasudevan D

Jan 28, 2018

Too much concepts to learn and practice. Course material can be little more engaging and split accordingly.

교육 기관: Maxim M

Dec 10, 2017

Very difficult lectures. You need a solid statistical background to keep up with the pace of the professor.

교육 기관: Simon

Mar 02, 2017

The ideas and concepts explained here are really important but are explained/written in a bit messy manner.

교육 기관: xuwei l

Sep 22, 2016

lectures notes is not details enough, had to google around other materials to grasp the courser work better

교육 기관: Rezoanoor/CS/Rezoanoor R

Mar 13, 2020

It covers a lot of topics, good for that but submitting assignment via Swirl is extremely boring.

교육 기관: manuel s g

Jul 05, 2020

This is module where I have learn less. Instructor also was not dynamic as previous ones.

교육 기관: Codrin K

Mar 05, 2018

Too bad it all starts from mathematical theorey; I would prefer a problem based approach.

교육 기관: Alex F

Feb 12, 2018

Very detailed and a little painful :) but I am sure it will be useful information

교육 기관: Lindsay S

Mar 02, 2017

These are complex topics, and just the quick overview doesn't fully explain them.

교육 기관: Gibson W

Feb 10, 2016

Not one a statistics newbie should take, had to take it twice just to grasp 80%

교육 기관: Bernardo D F d S

May 20, 2016

Content runs a bit fast but good course for stat inference with R focus.

교육 기관: Chunyue Z

Jun 16, 2019

The materials are not so clear to someone who's not familiar with stat.

교육 기관: Ali M

May 03, 2017

Concepts weren't explained properly. The instructor was going too fast.

교육 기관: Tomasz J

May 04, 2016

It's quite involved, fast and not explained thoroughly in some places.

교육 기관: Sergey

Jun 13, 2017

Unfortunately, the manner of presenting information desires the best.

교육 기관: Sushil K

May 10, 2016

Steep Learning Curve. Swirl exercises are important for this course

교육 기관: B S

Apr 25, 2018

Less good than expected. Explanations could be more clear.

교육 기관: Pulkit K

May 26, 2018

I don't like the example and the explanation at all.

교육 기관: Jim M

Jun 07, 2020

Great material, but could be better organized.

교육 기관: Thomas F

May 31, 2018

really bad review criteria for grading peers.

교육 기관: chris

Jul 11, 2017

Heavy content to cover in such a short time

교육 기관: Ram K P

Aug 03, 2018

Most lessons lack clarity. very evasive

교육 기관: Lei M

Aug 23, 2017

The stuff is very high leveled for me.

교육 기관: Tom C

Sep 16, 2018

Would be better if taught with Python