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추론적 통계(으)로 돌아가기

듀크대학교의 추론적 통계 학습자 리뷰 및 피드백

4.8
별점
2,422개의 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

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!

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!!!

필터링 기준:

추론적 통계의 434개 리뷰 중 351~375

교육 기관: Lucia F M D C

2021년 7월 15일

great

교육 기관: Praveen S

2020년 6월 3일

Super

교육 기관: Charles G

2018년 1월 20일

Great

교육 기관: Jenard J P P

2021년 2월 5일

yeah

교육 기관: Gonzalo C S

2016년 7월 24일

Cool

교육 기관: John C L R

2021년 4월 19일

g

교육 기관: Sanan I

2020년 6월 4일

.

교육 기관: Saravanan

2019년 1월 31일

-

교육 기관: Radoslaw T

2018년 3월 18일

O

교육 기관: Emanuele M

2020년 8월 18일

Overall a great course. Very rich in material. I do not have a strong math or statistical background and i struggled a bit with the range and quantity of material presented. Hard work is surely involved, but it is ultimately rewarding. A word of caution : if you are taking this course standalone (or as part of Coursera's Data Science Learning Path like me) without taking the first introductory part, you will have to compensate a bit on the programming parts if you are new to R (luckily a lot of freely available instructional material is found on the web, and the professor herself offers a free statistics textbook with online R labs). Not a downside for me, as this course has made me discover this fantastic language which has taken a strong position besides my budding Python skills. Cheers!

교육 기관: Wu X

2020년 4월 7일

I gave this course 4 stars. The missing 1 star is because this course has no content about R (but it is in a specialization called "statistics and R"). This course is only about statistics and the videos and instructor is good. The instructor explained the complex concepts well. At the end of the course, you need to do a project with Rstudio. I had no idea how to clean and manipulate the dataset and I had to drop out this course for sometime and register an account in another online education platform for programming for R specifically and learn how to handle those string, manipulate the datagrams and tables and extract the data I need from a dataset with thousands of variables. And then I got back to this project with more confidence and finally finished that.

교육 기관: Gabriel V

2022년 8월 1일

I​t is a very interesting take on inferential statistics. The statistics is taugth at introductory level, using the book Open Statistics that has been introduced in the first course in the series. Regarding the software, the course continues on the use of R and the tidyverse. I understand pipes and are comfortable in R, but I think it may be a little bit confusing if it is your first rodeo with the software.

I​'d recomend to include more resources about R in the course materials, or including those on the Open Statistics book. Also the book has many examples, but I would add at the end of the chapter a summary of the theory and formulas, since it is difficult to browse for refreshing the knowledge.

교육 기관: Gayatri L

2022년 3월 9일

I think overall this course was pretty good in explaining the concepts. Probably the best I've seen yet on this topic ans no other course I've even taken has helped me this much.

The only reason why I'm not giving it 5 stars is because I think they haven't taught much in terms of R. I think anyone who doesn't have any background on R at all might struggle with comlpeting the peer assignments and even the R sections in this course. I have a very basic idea so it helped a little but even I left it wsas an uphill battle there.

Still overall it's a course I would recommend to everyone just because of how well things are explained in this course. Everything is really very well sought out.

교육 기관: Jason L

2021년 1월 1일

This is a great course and Professor Çetinkaya-Rundel is a fantastic teacher. I feel much more confident with statistical concepts and really feel confident with calculating statistical tests by hand.

However, I feel less confident with the R part of the course. I often found myself having to Google functions to figure out how they worked. I would have appreciated more focus on R within the lectures themselves and not just in the labs. Other than that, this was a wonderful course and I learned so much.

교육 기관: Fernando M M E

2021년 7월 3일

A​ very useful course to refresh inferential statistics. If you don't have a minimal knowledge or if you don't remember anything, you will need more time to complete it. The book is clear and there are a lot of exercises, but if you read it and you do the exercises you will need much more time. For those doing it for the data science learning path, R is not very well explained, because this is the second course in a specialization of five courses in Statistics with R. The teacher teaches well.

교육 기관: Lucy M

2020년 5월 22일

Well structured course to take at your own pace. I did a stats course about 5 years ago and this has been a good refresher - not sure how hard it would be for a total novice - i think it would take more time than suggested. Warning, if like me you have prior experience in R the assignments will take a little more figuring out too. The discussion forums have most the answers and help you need and actually the peer-review is really helpful to 'learn by teaching'.

교육 기관: Shahin A

2016년 10월 1일

Some parts are needed more clarification. In other words, as a student of the course you need to go beyond the materials, since the materials are not self-sufficient. Specially about simulation methods. However, this is not the reason that I give the course 4 out of 5. The absence of any help from TAs, based on my experience, is the reason. I expected some official replies to my question while there are only a few question for each week of the course.

교육 기관: Janio A M

2018년 7월 28일

Great material although I will like to know more about the practical side of statistical inference. For instance, I have more of less an idea of how to use chi-squared test with categorical variables in a dataset however, for the other statistical inference methods such as p-values and confidence intervals I still don't see where can I use this methods when doing data analysis. Can we use this to detect outliers in our dataset for instance?

교육 기관: Chutian Z

2020년 4월 16일

Better than the Basic Statistics offered by the University of Amsterdam. That course was too informal, didn't address the techniques and covered too few materials. I love the fact that there are accompanying R labs. However, the course should teach the students the more general R functions (qt,pt,qnorm,etc.) instead of the self-developed "inference" function. In addition, it's a little hasty in week 4. The pace should slow down.

교육 기관: Amy W

2019년 12월 12일

The course is well designed, and the examples given in each lesson are informative and interesting.

For the final project, I wanted to group some categories from one variable together in a new variable, but I did not have the code I needed to do it. It would have been very helpful to have that information in one of the labs prior to doing the final project.

교육 기관: LEE K

2022년 8월 2일

Really useful course

I'm beginner at both R and statistics but It wasn't so hard to understand concepts

but it seems that professors or TAs don't really care about this course.

1. one RMD file was expried so that i couldn't kint document

2. almost no TA's answers for questions on discussion fourm

교육 기관: Richard N B A

2016년 6월 19일

Thorough treatment of the topics with great examples using real data. On the down side, the treatment of the mathematics behind the formulas is a little light. Great use of simulation to support the theory or to use when theoretical assumptions are not met. Strongly recommended!

교육 기관: Anna D

2017년 5월 22일

I loved this course. As with the previous course a lot of things that weren't clear to me before are now. I totally recommend it to anybody new to statistics or anybody who is struggling with statistics (like I have for a very long time).

교육 기관: Robert S

2017년 12월 27일

Very good material which gives practical knowledge supported by interesting examples. The only concern is that it is slightly shallow - lacking some mathematical justification for the given "rules of thumb" and theorems.

교육 기관: Farsan R

2016년 9월 29일

Very good introductory course for inferential statistics. It is wise to complete the first course Introduction to Probability and Data of this specialization before enrolling into this one to grasp the concepts.