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추론적 통계(으)로 돌아가기

듀크대학교의 추론적 통계 학습자 리뷰 및 피드백

4.8
별점
2,424개의 평가

강좌 소개

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...

최상위 리뷰

ZC

2017년 8월 23일

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

MN

2017년 2월 28일

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

필터링 기준:

추론적 통계의 435개 리뷰 중 401~425

교육 기관: Robert F

2016년 8월 8일

Nice introduction to statistical inference concepts and techniques

교육 기관: Shalabh S

2017년 5월 31일

Very nice coarse for learning methods of inferential statistics.

교육 기관: Aravindan V

2018년 9월 2일

Very well structured.Could focus on R programming a bit more!

교육 기관: romen a

2020년 5월 10일

¡Es una pena que no se traten más contenidos! Está genial

교육 기관: Veeraraghavan V

2018년 3월 5일

Need to revisit few classes as it was little aggressive.

교육 기관: Dgo D

2017년 2월 22일

Its a very good way to introduce to R language

교육 기관: SAURAV P

2016년 10월 29일

good powerful insight into statistics. Thanks!

교육 기관: Takahiro M

2017년 3월 5일

This is great course as Intro to Statistics

교육 기관: Sujhan D

2021년 8월 13일

could be made a little more interesting

교육 기관: Nathan H

2017년 12월 26일

I wish there was more exposure to R.

교육 기관: José M C

2017년 1월 4일

Very useful tools for inference

교육 기관: Yu X S

2021년 2월 14일

Too hard for beginners.

교육 기관: YUJI H

2017년 12월 28일

It is very difficult...

교육 기관: Nikolaos I

2022년 3월 26일

very poor contend on R

교육 기관: vineet r p

2021년 2월 12일

It was a great course

교육 기관: FERRIOL , S A (

2021년 4월 26일

Very helpful

교육 기관: Ananda R

2017년 3월 12일

excellent

교육 기관: joao b p d s

2018년 3월 9일

excelent

교육 기관: Shawn G

2017년 4월 20일

I would give it a 3.5, with the extra 0.5 because of the great interaction, ease of use, and clarity of progress. It was pretty hard for me and I barely made it in under the deadline (jumping session to session to complete). You definitely need some R background by the end for the project. I expected to get more in information in using R for inferential statistics too... though there was a presentation and each lesson had followup for use in R. Great use of examples for each section. That helped me a lot.

교육 기관: Raffaele S

2018년 11월 8일

The fundamental concepts of statistics are well explained, however the exercises involvig R are kinda rushed up. Moreover, the R part is accomplished mainly by a library, dplyr, and the main concepts of R as a programming language are skipped. Finally, the peer grade review is a little more advanced than the course lessons and takes really a painful process - but this is a common problem in coursera.

교육 기관: Cezary K

2017년 6월 30일

For me there is not much more than u could learn in comparison to previous course. Would expect some more knowledge from this course

교육 기관: mark n

2018년 7월 18일

great instruction on statistics, but no lectures on R. The R portion of the class is given as a lab at the end of each week.

교육 기관: Luke F

2017년 5월 18일

The lady could have used a bit more rehearsing before recording.

교육 기관: Willian W

2018년 3월 31일

Too much basic

교육 기관: Keith B L S

2022년 4월 4일

Good job!