Inferential Statistics
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
This Specialization is crafted to take beginners in this field from start to building functional prototypes, home projects, and new creations with custom peripheral hardware and a Raspberry Pi. If... more
In this project we are going to learn about lambda expressions and it\'s application in python. We are going to start with what is Lambda expression and how we can define it, comparing lambda... more
This Specialization is designed for professionals, educators, and lifelong learners seeking to enhance their critical thinking skills through neuroscience-based strategies. Across four courses, you... more
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will extend the single node EOSIO blockchain to use multiple nodes. You will install various EOSIO software... more
By the end of this project, you will have created a Visual Tasks Guide to use with your students. As teachers, we are always looking for ways to help our students grow. For students with special... more
Powered by
