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Course

Experimental Design in R

Intermediate

4.5+

Updated 03/2025

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

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RProbability & Statistics4 hours13 videos53 Exercises4,450 XP18,018Statement of Accomplishment

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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!

Prerequisites

Hypothesis Testing in R

1

Introduction to Experimental Design

Introduction to experimental design

A basic experiment

Randomization

Replication and blocking

Replication

Hypothesis testing

One sided vs. Two-sided tests

pwr package Help Docs exploration

Power & Sample Size Calculations

2

Basic Experiments

ANOVA, single, and multiple factor experiments

Exploratory Data Analysis (EDA) Lending Club

How does loan purpose affect amount funded?

Which loan purpose mean is different?

Multiple Factor Experiments

Model validation

Pre-modeling EDA

Post-modeling validation plots + variance

Kruskal-Wallis rank sum test

A/B testing

Which post-A/B test test?

Sample size for A/B test

Basic A/B test

A/B tests vs. multivariable experiments

3

Randomized Complete and Balanced Incomplete Block Designs

Intro to NHANES and sampling

NHANES dataset construction

NHANES Data Cleaning

Resampling NHANES data

Randomized Complete Block Designs (RCBD)

Which is NOT a good blocking factor?

Drawing RCBDs with Agricolae

NHANES RCBD

RCBD Model Validation

Balanced Incomplete Block Designs (BIBD)

Is a BIBD even possible?

Drawing BIBDs with agricolae

BIBD - cat's kidney function

NHANES BIBD

4

Latin Squares, Graeco-Latin Squares, and Factorial Experiments

Latin squares

NYC SAT Scores EDA

Dealing with Missing Test Scores

Drawing Latin Squares with agricolae

Latin Square with NYC SAT Scores

Graeco-Latin squares

NYC SAT Scores Data Viz

Drawing Graeco-Latin Squares with agricolae

Graeco-Latin Square with NYC SAT Scores

Factorial experiments

NYC SAT Scores Factorial EDA

Factorial Experiment with NYC SAT Scores

Evaluating the NYC SAT Scores Factorial Model

What's next in experimental design?

Experimental Design in R

Course
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Included withPremium or Teams

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*4.5

from 31 reviews

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Most recent
Top reviews

Rafal

about 4 hours

Ana-Maria

2 days

Keith

about 9 hours

Ramachandran

1 day

Keah

5 days

Karen

3 days

I still don't get what you re going to do in the end with the designed 'experimental designs' from the agricolae package. It is not used in the analysis.

Rafal

Ana-Maria

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