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
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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!
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!!!
This course is an excellent overview of inferential statistic tests / hypothesis tests and confidence intervals. The organization and material is quite good, with exercises and applications using R.
Awesome. I loved the way this course is done. I know what Test Statistic to use for what type of data and under which conditions. I am preparing a cheat-sheet that will be shared with all later on.
Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!
The concepts are explained in a very simple and effective manner with the help of a case study. Background knowledge of R will be very handy if one wants to cover the topics at a faster rate.
The professor is one of the best instructers I've seen. I've struggled to understand these concepts before but this course just set everything straight. Lots of content to practice with too.
I learnt a lot about inferential statistics from this course. It help me to understand better why I used one inferential method instead of another, and the assumptions and conditions.
This was hard; The Statistics part became harder and harder and the R part seemed to not keep up with it. You need to learn more R on your own, which is a challenge - there are man
I really enjoyed this course and found the professors lectures better structured and clearer. I also like (and needed) the variety of datasets she used for instruction. Thank you!!
What I learned best is not the formula, but the approach to test the conditions, the discussion of source of potential bias, the selection of inferential statistics methods.
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.
關於 Statistics with R 專項課程
Cost of the Course
If you want to complete the course and earn a Course Certificate by submitting assignments for a grade, you can upgrade your experience by subscribing to the course for $49/month. You can also apply for financial aid if you can't afford the course fee.
When you enroll in a course that is part of a Specialization (which this course is), you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses or cancel your subscription once you complete the single course.
Can I just enroll in a single course? I'm not interested in the entire Specialization.
To enroll in an individual course, search for the course title in the catalog.
To get full access to a course, including the option to earn grades and a Course Certificate, you'll need to subscribe. New subscribers will start with a full access subscription, which includes full access to every course in the Coursera catalog. Existing Specialization subscribers will be given the option to update to a full access subscription when enrolling in a new Specialization or course.
When you enroll in a course that is part of a Specialization, you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses.
Will I receive a transcript from Duke University for completing this course?
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.