Inferenzstatistik
About this Course
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 dataCreated by: Duke University
Related Online Courses
Welcome to Policy, Technology, and Carbon Free Cities, the second course in the Building Sustainable Cities Specialization. This course is intended to build upon foundational concepts introduced in... more
This course explores back-end infrastructure management, secure API design, and robust data protection techniques. Participants will gain practical skills in server configuration, API security, and... more
This lesson is part of a full course, Speak English Professionally: In Person, Online & On the Phone. Take this lesson to get a short tutorial on the learning objectives covered. To dive deeper... more
At the end of this project, you will have all the basic skills to create a professional and attractive pitch deck to present your project using Canva, an online tool for creating and editing... more
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We\'ll learn about reading, storing, and processing... more
Powered by
