About this course: 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. You will analyze multiple data sets using recipes given to you in the R statistical programming language -- no prior programming experience is assumed or required, but you will be required to read, understand, and modify code snippets provided to you. By the end of the course, you will be able to knowledgeably design, run, and analyze your own experiments that give statistical weight to your designs.

Who is this class for: This class is at the level of advanced undergraduates or first-year graduate students in fields related to human-computer interaction, computer science, interaction design, user experience design, user-centered design, or human-technology behavior studies.

Created by: University of California, San Diego

Taught by: Scott Klemmer, Associate Professor
Cognitive Science & Computer Science
Taught by: Jacob O. Wobbrock, Associate Professor
The Information School

Basic Info	Course 7 of 8 in the Interaction Design Specialization.
Commitment	9 weeks, 3-4 hours/week
Language	English
How To Pass	Pass all graded assignments to complete the course.
User Ratings	3.6 stars Average User Rating 3.6See what learners said

Syllabus

WEEK 1

Basic Experiment Design Concepts

In this module, you will learn basic concepts relevant to the design and analysis of experiments, including mean comparisons, variance, statistical significance, practical significance, sampling, inclusion and exclusion criteria, and informed consent. You’ll a...

2 videos, 1 reading

Graded: Understanding the Basics

WEEK 2

Tests of Proportions

In this module, you will learn how to analyze user preferences (or other tallies) using tests of proportions. You will also get up and running with R and RStudio. Topics covered include independent and dependent variables, variable types, exploratory data anal...

7 videos

Graded: Understanding Tests of Proportions

Graded: Doing Tests of Proportions

WEEK 3

The T-Test

In this module, you will learn how to design and analyze a simple website A/B test. Topics include measurement error, independent variables as factors, factor levels, between-subjects factors, within-subjects factors, dependent variables as responses, response...

2 videos

Graded: Understanding Experiment Designs

Graded: Doing Independent-Samples T-Tests

WEEK 4

Validity in Design and Analysis

In this module, you will learn about how to ensure that your data is valid through the design of experiments, and that your analyses are valid by understanding and testing for their assumptions. Topics include how to achieve experimental control, confounds, ec...

4 videos

Graded: Understanding Validity

Graded: Doing Tests of Assumptions

WEEK 5

One-Factor Between-Subjects Experiments

In this module, you will learn about one-factor between-subjects experiments. The experiment examined will be a between-subjects study of task completion time with various programming tools. You will understand and analyze data from two-level factors and three...

3 videos

Graded: Understanding Oneway Designs

Graded: Doing Oneway ANOVAs

WEEK 6

One-Factor Within-Subjects Experiments

In this module, you will learn about one-factor within-subjects experiments, also known as repeated measures designs. The experiment examined will be a within-subjects study of subjects searching for contacts in a smartphone contacts manager, including the ana...

5 videos

Graded: Understanding Oneway Repeated Measures Designs

Graded: Doing Oneway Repeated Measures ANOVAs

WEEK 7

Factorial Experiment Designs

In this module, you will learn about experiments with multiple factors and factorial ANOVAs. The experiment examined will be text entry performance on different smartphone keyboards while sitting, standing, and walking. Topics include mixed factorial designs, ...

4 videos

Graded: Understanding Factorial Designs

Graded: Doing Factorial ANOVAs

WEEK 8

Generalizing the Response

In this module, you will learn about analyses for non-normal or non-numeric responses for between-subjects experiments using Generalized Linear Models (GLM). We will revisit three previous experiments and analyze them using generalized models. Topics include a...

2 videos

Graded: Understanding Generalized Linear Models

Graded: Doing Generalized Linear Models

WEEK 9

The Power of Mixed Effects Models

In this module, you will learn about mixed effects models, specifically Linear Mixed Models (LMM) and Generalized Linear Mixed Models (GLMM). We will revisit our prior experiment on text entry performance on smartphones but this time, keeping every single meas...

4 videos

Graded: Understanding Mixed Effects Models

Graded: Doing Mixed Effects Models

FAQs

How It Works

Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators

University of California, San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.

Pricing

	Audit	Purchase Course
Access to course materials	Available	Available
Access to graded materials	Not available	Available
Receive a final grade	Not available	Available
Earn a shareable Course Certificate	Not available	Available

Ratings and Reviews

Rated 3.6 out of 5 of 210 ratings

Is a wonderful course!!!

Extremely Practical Course. Lots of statistical detail & breadth of tests.

The video lectures and the r code supplied are of excellent quality, and the concepts were explained in a very simple and concise way. Despite this, the Professors' participation in the Discussion Forums was nonexistent, which in some cases was very necessary since some of the quizzes required some explanation.

It was very helpful for me, thank you! I thought that I will never be able to make this challenging course, but after completion I think that I have courage to design, run and analyze experiments on practice!

Share

Designing, Running, and Analyzing Experiments

Designing, Running, and Analyzing Experiments

Designing, Running, and Analyzing Experiments