Chevron Left
返回到 Inferential Statistics

Inferential Statistics, Duke University

4.8
1,147 个评分
221 个审阅

课程信息

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...

热门审阅

创建者 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!!!

创建者 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!

筛选依据:

216 个审阅

创建者 Hidetake Takahashi

Dec 03, 2018

nice course. it will definitely gives you skill.

创建者 Luis Felipe Sanchez Sanabria

Dec 01, 2018

It was a great course, one of the best things was the R programming for statistical test and inference.

创建者 Toan Thien Le

Nov 30, 2018

Yet another superb course in this specialization.

Be ready to spend lots of time and learn lots of things.

创建者 Zhang Qianming

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

创建者 Chanuwas Aswamenakul

Nov 21, 2018

The course is very useful and helps me understand the formal testing process of data analysis. I just hope it would cover more of non-parametric testing techniques and dive into a bit more into effect size testing. Anyway, It also provides a lot of insights into important statistical measures of information, which could potentially be extended to the field of predictive modeling and machine learning.

创建者 Umair Rafique

Nov 21, 2018

Excellent teaching style with enough practice to get a good grip on whatever is taught

创建者 Mrinalini Sharma

Nov 19, 2018

This is a very well structured and taught course. It is difficult so make sure to dedicate lots of time for videos, practice, and revisions.

创建者 Peter Chriske

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.

创建者 Eyuel Melese Muse

Nov 17, 2018

Just Great!

创建者 Alain Craven

Nov 17, 2018

The best course I have ever done on coursera!

Simpy perfect