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ANOVA and Experimental Design

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ANOVA and Experimental Design

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Gain insight into a topic and learn the fundamentals.
3.9

21 reviews

Intermediate level

Recommended experience

Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
Build toward a degree
Gain insight into a topic and learn the fundamentals.
3.9

21 reviews

Intermediate level

Recommended experience

Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
Build toward a degree

What you'll learn

  • Identify and interpret the two-way ANOVA (and ANCOVA) model(s) as a linear regression model.

  • Use the two-way ANOVA and ANCOVA models to answer research questions using real data.

  • Define and apply the concepts of replication, repeated measures, and full factorial design in the context of two-way ANOVA.

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Assessments

24 assignments

Taught in English

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This course is part of the Statistical Modeling for Data Science Applications Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

This second course in statistical modeling will introduce students to the study of the analysis of variance (ANOVA), analysis of covariance (ANCOVA), and experimental design. ANOVA and ANCOVA, presented as a type of linear regression model, will provide the mathematical basis for designing experiments for data science applications. Emphasis will be placed on important design-related concepts, such as randomization, blocking, factorial design, and causality. Some attention will also be given to ethical issues raised in experimentation.

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from photo by Vincent Ledvina on Unsplash

In this module, we will introduce the basic conceptual framework for experimental design and define the models that will allow us to answer meaningful questions about the differences between group means with respect to a continuous variable. Such models include the one-way Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA) models.

What's included

9 videos4 readings9 assignments2 programming assignments1 peer review1 discussion prompt2 ungraded labs

9 videos•Total 87 minutes
  • Introduction to Experimental Design•10 minutes
  • The One-Way ANOVA and ANCOVA Models•6 minutes
  • ANOVA Variance Decomposition•9 minutes
  • ANOVA Sums of Squares and the F-test•14 minutes
  • ANOVA and ANCOVA as Regression Models•10 minutes
  • One-Way ANOVA Interpretation in the Regression Context•10 minutes
  • The ANCOVA Model•15 minutes
  • ANCOVA with Interactions•7 minutes
  • ANCOVA with Interactions in R•5 minutes
4 readings•Total 31 minutes
  • Course Updates and Accessibility Support•1 minute
  • Earn Academic Credit for your Work!•10 minutes
  • Course Support•10 minutes
  • Assessment Expectations•10 minutes
9 assignments•Total 270 minutes
  • Introduction to ANOVA and Experimental Design•30 minutes
  • The One-Way ANOVA and ANCOVA Models•30 minutes
  • ANOVA Variance Decomposition•30 minutes
  • ANOVA Sums of Squares and the F-Test•30 minutes
  • ANOVA and ANCOVA as Regression Models•30 minutes
  • One-Way ANOVA Interpretation in the Regression Context•30 minutes
  • The ANCOVA Model•30 minutes
  • ANCOVA with Interactions•30 minutes
  • ANCOVA with Interactions in R•30 minutes
2 programming assignments•Total 120 minutes
  • Module 1 Autograded•60 minutes
  • Optional Introduction to Jupyter and R•60 minutes
1 peer review•Total 60 minutes
  • Module 1 Peer-Review Submission•60 minutes
1 discussion prompt•Total 10 minutes
  • Introduce Yourself•10 minutes
2 ungraded labs•Total 120 minutes
  • ANCOVA with Interactions in R•60 minutes
  • Module 1 Peer-Review Lab•60 minutes

In this module, we will learn how statistical hypothesis testing and confidence intervals, in the ANOVA/ANCOVA context, can help answer meaningful questions about the differences between group means with respect to a continuous variable.

What's included

6 videos2 readings4 assignments1 programming assignment1 peer review2 ungraded labs

6 videos•Total 91 minutes
  • Beyond the Full F-test•12 minutes
  • Planned Comparisons: Defining Contrasts•17 minutes
  • Planned Comparisons: Hypothesis Testing with Contrasts•14 minutes
  • Post Hoc Comparisons•14 minutes
  • Post Hoc Comparisons in R•17 minutes
  • Type II Error and Power in the ANOVA Context•19 minutes
2 readings•Total 20 minutes
  • Patrizio E. Tressoldi and David Giofré: "The pervasive avoidance of prospective statistical power: major consequences and practical solutions"•10 minutes
  • Optional: Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors•10 minutes
4 assignments•Total 120 minutes
  • Beyond the Full F-test•30 minutes
  • Planned Comparisons: Defining Contrasts•30 minutes
  • Planned and Unplanned Comparisons•30 minutes
  • Type II Error and Power in the ANOVA Context•30 minutes
1 programming assignment•Total 120 minutes
  • Module 2 Autograded Assignment•120 minutes
1 peer review•Total 60 minutes
  • Module 2 Peer-Review Submission•60 minutes
2 ungraded labs•Total 120 minutes
  • Planned Comparisons Using Contrasts in R•60 minutes
  • Module 2 Peer-Review Lab•60 minutes

In this module, we will study the two-way ANOVA model and use it to answer research questions using real data.

What's included

7 videos6 assignments1 programming assignment1 peer review1 ungraded lab

7 videos•Total 79 minutes
  • Motivating the Two-way ANOVA Model•11 minutes
  • The two-way ANOVA model•10 minutes
  • The Two-way ANOVA Model as a Regression Model•9 minutes
  • Interaction Terms in the Two-way ANOVA Model: Definitions and Visualizations•14 minutes
  • Interactions in the Two-way ANOVA Model: Formal Tests•15 minutes
  • Two-way ANOVA Hypothesis Testing (no interaction)•15 minutes
  • Looking Ahead: Two-Way ANOVA and Experimental Design•5 minutes
6 assignments•Total 180 minutes
  • Motivating the Two-way ANOVA Model•30 minutes
  • The Two-way ANOVA Model•30 minutes
  • The Two-way ANOVA Model as a Regression Model•30 minutes
  • Interaction Terms in the Two-way ANOVA Model: Definitions and Visualizations•30 minutes
  • Interactions in the Two-way ANOVA Model: Formal Tests•30 minutes
  • Two-way ANOVA Hypothesis Testing (no interaction)•30 minutes
1 programming assignment•Total 180 minutes
  • Module 3 Autograded Assignment•180 minutes
1 peer review•Total 60 minutes
  • Module 3 Peer-Review Submission•60 minutes
1 ungraded lab•Total 60 minutes
  • Module 3 Peer-Review Lab•60 minutes

In this module, we will study fundamental experimental design concepts, such as randomization, treatment design, replication, and blocking. We will also look at basic factorial designs as an improvement over elementary “one factor at a time” methods. We will combine these concepts with the ANOVA and ANCOVA models to conduct meaningful experiments.

What's included

7 videos2 readings5 assignments1 programming assignment1 peer review2 ungraded labs

7 videos•Total 79 minutes
  • The Conceptual Framework of Experimental Design•19 minutes
  • The Completely Randomized Design•13 minutes
  • The Randomized Complete Block Design (RCBD)•8 minutes
  • The Randomized Complete Block Design (RCBD): Hypothesis Testing•8 minutes
  • The Factorial Design•11 minutes
  • Further Issues in Experimental Design•7 minutes
  • Ethical Issues in Experimental Design•13 minutes
2 readings•Total 20 minutes
  • Causation and Experimental Design•10 minutes
  • Resources on Ethics •10 minutes
5 assignments•Total 150 minutes
  • The Conceptual Framework of Experimental Design•30 minutes
  • The Completely Randomized Design•30 minutes
  • The Randomized Complete Block Design (RCBD)•30 minutes
  • The Factorial Design•30 minutes
  • Further Issues in Experimental Design•30 minutes
1 programming assignment•Total 120 minutes
  • Module 4 Autograded Assignment•120 minutes
1 peer review•Total 60 minutes
  • Module 4 Peer-Review Submission•60 minutes
2 ungraded labs•Total 180 minutes
  • A Completely Randomized Design (CRD) in R•60 minutes
  • Module 4 Peer-Review Lab•120 minutes

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This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

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4.2 (10 ratings)
University of Colorado Boulder
5 Courses•15,369 learners

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ZC
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Reviewed on Jul 30, 2022

Great course. Really useful and practical, and the exercise is not too difficult.

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