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Voltar para Estatística Inferencial

Comentários e feedback de alunos de Estatística Inferencial da instituição Universidade Duke

4.8
estrelas
2,290 classificações
419 avaliações

Sobre o curso

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...

Melhores avaliações

MN
28 de Fev de 2017

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
23 de Ago de 2017

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!!!

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26 — 50 de 414 Avaliações para o Estatística Inferencial

por Jamison T

5 de Jul de 2018

I should not be charged if I have completed the project and simply waiting for other users to review it. This is dependent on how many users are taking the course at any given time. A bad system that results in users paying more for uncontrollable uncertain factors...

por Danielle B

14 de Fev de 2021

As with the previous course in this specialization, the statistics instruction is quite good. The R instruction is almost non-existent. You can expect to spend plenty of time on your own, Googling the skills you'll need to complete your end project.

por Piotr Z

7 de Jun de 2020

The course was not very helpful for me, as practical cases with R were poorly developed and the final data capstone project is badly formulated which makes it extremely difficult to pass.

por R. R

9 de Set de 2020

Lots of perplexing questions in their assignments, and the quizzes were too difficult. However, I garnered modest skills in this program.

por THEJUS S

29 de Ago de 2020

Such a worst course never seen in my life

por Rui Z

14 de Mai de 2019

Professor Mine is terrific. I'm sure she has a great depth of knowledge and grateful that she's able to deliver her knowledge out to listeners. She uses meaningful examples all along the course, no dry pure mathematical cases at all. That helps a ton to digest concepts. And she constantly repeat some core concepts and how to interpret a statistic right. I didn't realize how important this was until I was challenged with questions, then I came back and hear again her interpretation, and the whole thing became clearer. She's one of the best professors I've ever listened to, and I've been through grad school, met so many professors.

The current mentor Rolf was great at supporting. He answers a lot of questions in the forum. He's very responsible and supportive. So if you're considering on taking this course, take it now as mentor will change!

I haven't finished the course yet, but the enrollment rate seems to be quite decent, so I wouldn't expect it to take too long to get final project reviewed and get certificate. I assume this is an important issue for any course takers.

The only downside is that there could be more R code teaching, especially on complicated simulations. That way it may be more friendly to R beginners. I know it's important to do research ourselves for codes, but beginners could lack of proper terminology or vision by nature to do the research on Google. Especially when I'm physically in the Main Land of China, where it takes some efforts to even get on Google, so doing code research took a lot of my time and was a little frustrating towards the end.

But again, the overall course and support are great! If this is not a 5 start course, I can hardly give out my highest mark to any other courses. It helped me to understand inferencial statistics, practice R, and think more like a statistician.

por Hao C

6 de Nov de 2019

Teaching: I really like the clear and concise teaching style of lecturer and the wide range of simple real-life example used to explain the course content.

I’m a social science student. Although I’ve studied quantitative research methods before, this course gives me some new insights into inferential statistics. I think I will never forget the statistical meaning of p-value after this course!

Course Structure: The course structure is well organized with clear focus in each week.

The first and second weeks are easy to follow, but the third and fourth weeks are more challenging.

Textbook: The textbook used in this course is a good supplementary material, although it is not necessary to read the textbook. Course videos have already explained everything that we need to know at intro level. However, it is worth reading the textbook for the third and fourth weeks.

Assessment: The assessment of quiz in each week is relatively easy. The exploratory data analysis required in peer-reviewed assignment is slightly challenging, because it might be hard for beginners to touch every required point.

por Σταυρος Β

23 de Nov de 2021

I found the course material very interesting and adequate depth-wise. The weekly analysis projects with R were also very useful in drilling in the concepts and providing extra practice with programming.

Overall the focus is on statistics and not so much on R which means you will have to google your way at some point, although you can reuse what you learned in the weekly projects with R.

The instructor is also very good and makes sure to repeat concepts again and again throughout the course which helps a lot in digesting them.

Overall great course. Keep in mind of course that you'll get out as much as you put in it.

por Shobhit K

16 de Mai de 2021

Thank you so much! I learnt what I came to learn. Well curated and organized. Explores all potential areas of statistical inference and hypothesis testing and gives you a framework to relate between the two. Only feedback is to have one final conclusion/summary video where you can summarize how to use everything that we have learned based on the type of variables and the question at hand, i.e. mapping the learned approaches to types of problems. It was available as a scoring criteria in reviewing peer assignments but would be great to have it as a separate concluding video/note as well.

por Tanika M

12 de Jun de 2020

I feel like I gained a solid foundation on inferential statistics from this course. I found the videos useful, with many well-explained examples. I would say that the readings should not be treated as optional - they were where I did the bulk of my learning. The scope of the final project is reasonable.

It may be relevant that I also took the previous course in this specialization, and I can see that not having done the previous labs would have made the project a little harder. As other reviews have said, the forums also seem much less moderated than the last course's.

por Jorge L

19 de Out de 2016

Terrific course, i got here after starting the Data Science specialization on John Hopkins uni on Coursera, but there bit on statistics is awful, a waste of time.

I decided to give Courser another shot and definitely not regretting it, this course really go over the basics clearly and make sure to make enough exercise to revisit that clearly explain the fundamentals.

I was happy as getting to the final assignment i found myself doing quite an advance analysis and inference that i notice i really understood the topics on the course.

por 이제민

6 de Ago de 2016

It has a little expensive tuition fee than other courses such as Data Science (Johns Hopkins) and Data life (HarvardX_edx). But I decided this course rather than choosing the others because I felt that it was well organized and quite good supplements. What I like most about this course is instructor. She looks like enthusiastic to give a her idea and wisdom. It attracts me to take this course even though it is expensive relatively. Anyway, I appreciate her for dedicated teaching in advance.

por Kuntal G

6 de Out de 2016

It is really the best Statistics course that i have ever done. After doing all the course in statistics i'm very much confident in statistics. The course and Specialization is very clear, concise, nice explanation with example videos to have better understanding of the theory. It is highly recommended course for anyone interested to learn statistics in their career. Please do the maximum the course in the specialization to have good grasp of statistics if you are beginner like me :)

por Emilio M

4 de Jun de 2020

Very concise and interesting. I was able to brush up many concepts. It is important to indicate to the students, that the materials provided are not enough to create a final project in a meaningful way.

This is because the code to use R is limited to the basics throughout the course. Extra or outside research is necessary to increase R skills.

Many students have technical difficulties, sometimes unusual. Is it possible to address them by expanding an FQA section?

por Dario B

6 de Nov de 2018

Very interesting material. Statistical inference was one of the great mysteries for me, and it is indeed a technical topic. But the professor does a great job in presenting the material in an intuitive way, giving an awesome introduction. Very interesting real examples too.

Looking forward to have a proof-based equivalent course, though maybe I should focus on a forma probability course first.

por Ondina F P

17 de Mai de 2019

Very good explained course, with lot of useful exercise, so you can be sure to understand the theory. Th practical examples in R are well designed and explained. This is definitely a must for someone interested in statistics, with beginning concepts that you need to keep in mind for further coursers. The teaches is also excellent, explanation and examples are very good. Recommended!

por John F W S

5 de Nov de 2016

I really enjoyed this course, it is pitched at just the right level for someone who is sometimes busy with part time work. It does ask that when you study, you study well. I've not learned any programming before these courses, so sometimes my knowledge of R is lacking. But it is rewarding to learn R to really see these statistical ideas come alive.

por Jose N d l R

25 de Mai de 2017

If you are new to this, get ready to sweat. This course teaches many many concepts and if you think that it tiptoes around it you will be surprised. You might walk away and forget some of the methods and tests since there are too many, but you won't get away without learning to interpret and reasoning absolutely everything that you compute or do.

por Igor S

5 de Mai de 2021

The course is well-paced, covers the relevant topics from the basics and gives you a bit of freedom on the project. The comments made for the first course in this series still stand: there is a lot of statistics and a little R. However, it is not as painful to code as it was during the first course (although still need to google a lot).

por Jesus

16 de Mai de 2016

Great course, the professor is able to explain and articulate complex ideas into a digestible manner. If you ever taken a statistics class you know would know how incredibly rare it is to have such a great professor able to explain the material as well as she does. Thanks you very much Dr. Mine Cetinkaya-Rundel for teaching this course.

por Bruno A

24 de Mar de 2020

Nice refresher course on inference testing, with a broad coverage of the types of variables / analyses.

Not heavy at all on the math side.

Students have to find their tips for R-coding on the Internet for the most part. It is a good way to learn! But we could use more standard tips from the course itself, especially on EDA.

por Jacob T

7 de Mai de 2019

The best online course I have taken so far. It teaches you all the statistical methods you need to do for inference. The lessons are well taught and organized in a way where each lesson builds off the previous. The final project is also a great way to put everything you learned throughout together.

por Amarendra S

26 de Fev de 2019

Had a great learning experience with in depth knowledge of statistics, inference and hypothesis. Structure of the course helped me grasp things in an organized way. The use of real time data to explain concepts had a great impact in making things easier to understand and relate to things around us.

por José J P A

4 de Jul de 2016

Excelente curso. Vale totalmente la pena tomarlo. Es muy importante atender la lectura sugerida y tomar notas. Complementando la platica junto con la lectura sugerida estoy seguro que tendrás las herramientas necesarias para iniciar un desarrollo en el ámbito de análisis de datos.

por Praneeth K

17 de Abr de 2017

The course is structured very well and has some great content, suitable for anyone who is just beginning with statistics in R or if you want a refresher on statistics. Dr. Milne is a great instructor, i have taken some other courses of her's and was never disappointed.