New Course: Experimental Design in R

[This article was first published on DataCamp Community - r programming, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Here is the course link.

Course Description

Experimental design is a crucial part of data analysis in any field, whether you work in business, health or tech. If you want to use data to answer a question, you need to design an experiment! In this course you will learn about basic experimental design, including block and factorial designs, and commonly used statistical tests, such as the t-tests and ANOVAs. You will use built-in R data and real world datasets including the CDC NHANES survey, SAT Scores from NY Public Schools, and Lending Club Loan Data. Following the course, you will be able to design and analyze your own experiments!

Chapter 1: Introduction to Experimental Design (FREE)

An introduction to key parts of experimental design plus some power and sample size calculations.

Chapter 2: Basic Experiments

Explore the Lending Club dataset plus build and validate basic experiments, including an A/B test.

Chapter 3: Randomized Complete (& Balanced Incomplete) Block Designs

Use the NHANES data to build a RCBD and BIBD experiment, including model validation and design tips to make sure the BIBD is valid.

Chapter 4: Latin Squares, Graeco-Latin Squares, & Factorial experiments

Evaluate the NYC SAT scores data and deal with its missing values, then evaluate Latin Square, Graeco-Latin Square, and Factorial experiments.

Prerequisites

To leave a comment for the author, please follow the link and comment on their blog: DataCamp Community - r programming.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)