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Kursteilnehmer-Bewertung und -Feedback für Inferential Statistics von Duke University

4.8
stars
1,563 Bewertungen
281 Bewertungen

Über den Kurs

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...

Top-Bewertungen

ZC

Aug 24, 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!!!

MN

Mar 01, 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!

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226 - 250 von 276 Bewertungen für Inferential Statistics

von Radoslaw T

Mar 18, 2018

O

von Shahin A

Oct 01, 2016

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.

von Janio A M

Jul 29, 2018

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?

von Amy W

Dec 12, 2019

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.

von Richard N B A

Jun 19, 2016

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!

von Anna D

May 22, 2017

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).

von Robert S

Dec 27, 2017

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.

von Farsan

Sep 29, 2016

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.

von robert p

Aug 28, 2018

This course seemed unbalanced compared to some of the other courses and was very work-heavy. I felt it could have, or maybe should have been broken up into two courses, or that other courses should be longer.

von Amit C

Feb 18, 2019

The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided

von Zhang Q

Nov 23, 2018

Very useful course about statistics. May need some fundamental understanding of statistics before, but through the clear explanation and examples, I've learnt a lot from this course

von Paul N

Aug 17, 2016

The teaching is good, the course is a little heavy and a lot to take in in the later weeks. But, as a further grounding for statistics and R, I would very much recommend it.

von Adara

Oct 17, 2017

It is a very nice course, I have learned a lot. However, it is convenient to take the previous one of the specialization, as they base some examples or R knowledge on it.

von Abiodun B

Mar 28, 2017

This course gave me the toughest time of my life. I did the course for 3 months, i failed project once but i thank God, i proved toughest by passing with 100%.

von Sergio E T

Jan 04, 2019

The inference function and hypotheses tests are really useful. Permutation tests need more explaining and examples; otherwise they should not be included.

von Aaron M

Nov 28, 2019

A good course for learning statistical inference, though I found that more than a week per module was required to really absorb the content.

von dumessi

Aug 13, 2019

It is a great course, while some underlying logics are not clearly explained. And the quiz has some unexplained context, which is confused.

von Janusz P

Apr 29, 2018

I liked this course because it gives basic ideas how inferential statistics works, without going into mathematical details.

von Peter C

Nov 19, 2018

I thought this course did a great job of incorporating R code into the lecture and hope that continues in future courses.

von Richard M

Mar 08, 2019

Generally a great course, but would benefit from a better explanation at times of how to use R effectively.

von Markus K

Aug 18, 2017

Good videos, good book with exercises but many useful functions in R were not introduced (e.g. t.test()).

von kirran

Sep 06, 2018

More detailed answers on Quiz questions and some more explanation on R codes will help a lot

von Ghada S

Dec 12, 2019

I think it is a little bit difficult for someone who knows nothing about probability or R.

von mnavidad

Jun 15, 2018

This course is great learn a lot well explained, the professor is great!!!

von Robert F

Aug 08, 2016

Nice introduction to statistical inference concepts and techniques