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

4.8
1,527 Bewertungen
275 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

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!

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!!!

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201 - 225 von 271 Bewertungen für Inferential Statistics

von Ruben D S P

May 28, 2019

great class, I improved many Statistics skills and learned R at the same time

von Heungbak C

Jun 06, 2019

Very useful and meaningful lectures!

I learned many things from this course.

Thank you.

von Robin M

Jun 17, 2019

Great course, more difficult than the first module. The code was super useful to learn.

von David B J

Jun 21, 2019

Very nice job of explaining the material. I love the diverse set of examples used in the lectures and labs.

von Harkeerat S T

Jun 26, 2019

Very rigorous coursework. Loved the material.

von Mit P

Jul 08, 2019

Great learning experience. Very well crafted course. Thank you Dr. Rundel and the entire team of instructors!

von gerardo r g

Jul 23, 2019

awesome

von Eduardo M

Jul 25, 2019

Excellent!

von Tran T H

Aug 03, 2019

It is very helpful to me.

von Jacob T

May 07, 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.

von Amruta G

May 23, 2019

It's a great course! Helped me identify and clarify lots of concepts which I had understood just halfway in class.

von Nandkishore

Jun 12, 2019

seeking statistics inference through example in very convenient and easier way

von schlies

May 31, 2019

good course

von fatima s

Sep 13, 2019

Thank you Dr. Mine Çetinkaya-Rundel, you are the best teacher I ever had.

von Veliko D

Sep 18, 2019

Amazing course. Perfect balance between theory and practice!

von Parab N S

Sep 30, 2019

An excellent course by Professor Rundel on Inferential Statistics.

von Giulia T

Nov 12, 2019

Nice follow up from the previous course in the specialisation. The teacher is clear and the main concepts are reminded throughout the course and explained in good depth

von Nikhil K

Nov 15, 2019

This course was simply amazing.

von Bibek D

Nov 21, 2019

very informative course which was very easy to learn.....

von Soumya A

Nov 26, 2019

good learning

von Majeed K

Oct 15, 2019

An excellent course. Thank you Ms. Rundel

von Hao C

Nov 06, 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.

von Charlotte C

Oct 20, 2019

This is the second in the series with professor Çetinkaya-Rundel. She explains everything very well and makes the subject fascinating.

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 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.