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Experimental Design in R

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

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4 Hours12 Videos52 Exercises12,830 Learners4400 XPStatistician Track

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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!
  1. 1

    Introduction to Experimental Design

    Free

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

    Play Chapter Now
    Intro to experimental design
    50 xp
    A basic experiment
    100 xp
    Randomization
    100 xp
    Replication
    100 xp
    Blocking
    100 xp
    Hypothesis testing
    50 xp
    One sided vs. Two-sided tests
    100 xp
    pwr package Help Docs exploration
    50 xp
    Power & Sample Size Calculations
    100 xp

In the following tracks

Statistician

Collaborators

richie
Richie Cotton
beccarobins
Becca Robins
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DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of your browser with video lessons and fun coding challenges and projects.
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