Random Models, Nested and Split-plot Designs (Coursera)

Random Models, Nested and Split-plot Designs (Coursera)

Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. The course also covers experiments with nested factors, and experiments with hard-to-change factors that require split-plot designs.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

We also provide an overview of designs for experiments with response distributions from nonnormal response distributions and experiments with covariates.
What You Will Learn

  • Design and analyze experiments where some of the factors are random
  • Design and analyze experiments where there are nested factors or hard-to-change factors
  • Analyze experiments with covariates
  • Design and analyze experiments with nonnormal response distributions

Course 4 of 4 in the Design of Experiments Specialization.

Syllabus

WEEK 1: Experiments with Random Factors
WEEK 2: Nested and Split-Plot Designs
WEEK 3: Other Design and Analysis Topics

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Practical Time Series Analysis (Coursera) Coursera
The State University of New York

Practical Time Series Analysis (Coursera)

Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

Oct 5th 2026
5-12 Weeks
Civil Registration & Vital Statistics in Population Health (Coursera) Coursera
Johns Hopkins University

Civil Registration & Vital Statistics in Population Health (Coursera)

In this course, you will learn about the role and importance of civil registration and vital statistics (CRVS) systems that are used to track birth, death, and life events. Experts from around the world will explain what CRVS systems are, how they are used, the legal bases for registering vital events, and challenges experienced with CRVS systems.

Sep 28th 2026
2 Weeks
Designing, Running, and Analyzing Experiments (Coursera) Coursera
University of California, San Diego

Designing, Running, and Analyzing Experiments (Coursera)

You may never be sure whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design user-centered experiments, how to run such experiments, and how to analyze data from these experiments in order to evaluate and validate user experiences. You will work through real-world examples of experiments from the fields of UX, IxD, and HCI, understanding issues in experiment design and analysis.

Sep 21st 2026
5-12 Weeks
Aléatoire : une introduction aux probabilités - Partie 1 (Coursera) Coursera
École Polytechnique

Aléatoire : une introduction aux probabilités - Partie 1 (Coursera)

Ce cours d'introduction aux probabilités a la même contenu que le cours de tronc commun de première année de l'École polytechnique donné par Sylvie Méléard. Le cours introduit graduellement la notion de variable aléatoire et culmine avec la loi des grands nombres et le théorème de la limite centrale. Les notions mathématiques nécessaires sont introduites au fil du cours et de nombreux exercices corrigés sont proposés.

Oct 5th 2026
5-12 Weeks
Fundamentals of Engineering Exam Review (Coursera) Coursera
Georgia Institute of Technology

Fundamentals of Engineering Exam Review (Coursera)

The purpose of this course is to review the material covered in the Fundamentals of Engineering (FE) exam to enable the student to pass it. It will be presented in modules corresponding to the FE topics, particularly those in Civil and Mechanical Engineering. Each module will review main concepts, illustrate them with examples, and provide extensive practice problems.

Oct 5th 2026
5-12 Weeks
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera)

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.

Sep 21st 2026
5-12 Weeks
Introduction to Mathematical Thinking (Coursera) Coursera
Stanford University

Introduction to Mathematical Thinking (Coursera)

Learn how to think the way mathematicians do - a powerful cognitive process developed over thousands of years. Mathematical thinking is not the same as doing mathematics – at least not as mathematics is typically presented in our school system. School math typically focuses on learning procedures to solve highly stereotyped problems. Professional mathematicians think a certain way to solve real problems, problems that can arise from the everyday world, or from science, or from within mathematics itself.

Oct 5th 2026
5-12 Weeks
Math for MBA and GMAT Prep (Coursera) Coursera
Emory University

Math for MBA and GMAT Prep (Coursera)

This course gives participants a basic understanding of statistics as they apply in business situations. A fair share of students considering MBA programs come from backgrounds that do not include a large amount of training in mathematics and statistics. Often, students find themselves at a disadvantage when they apply for or enroll in MBA programs. This course will give you the tools to understand how these business statistics are calculated for navigating the built-in formulas that are included in Excel, but also how to apply these formulas in an range of business settings and situations.

Oct 5th 2026
5-12 Weeks
A Crash Course in Data Science (Coursera) Coursera
Johns Hopkins University

A Crash Course in Data Science (Coursera)

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.

Sep 21st 2026
1 Week
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions (Coursera) Coursera
Rice University

Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions (Coursera)

The abilities to understand and apply Business Statistics are becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers.

Sep 21st 2026
4 Weeks
Introduction to Statistics (Coursera) Coursera
Stanford University

Introduction to Statistics (Coursera)

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.

Oct 5th 2026
5-12 Weeks
Managing Uncertainty in Marketing Analytics (Coursera) Coursera
Emory University

Managing Uncertainty in Marketing Analytics (Coursera)

Marketers must make the best decisions based on the information presented to them. Rarely will they have all the information necessary to predict what consumers will do with complete certainty. By incorporating uncertainty into the decisions that they make, they can anticipate a wide range of possible outcomes and recognize the extent of uncertainty on the decisions that they make. In Incorporating Uncertainty into Marketing Decisions, learners will become familiar with different methods to recognize sources of uncertainty that may affect the marketing decisions they ultimately make.

Sep 21st 2026
4 Weeks