University of California San Diego
Designing, Running, and Analyzing Experiments
The only way to have an effective user experience is it with users.| Length | 1 to 3 months |
| Effort | 8-10 hours per week |
| Price | Free |
| Subject | Design, Computer Science |
| Level | Intermediate |
| Languages | English |
| Video Transcripts | Portuguese, Chinese, Russian, English, Spanish |
About this Course
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.
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.
What you'll learn
:
Experiment
Experimental Design
Statistical Model
R Programming
Statistics
Course syllabus
Week 1: Basic Experiment Design Concepts
Week 2: Tests of Proportions
Week 3: The T-Test
Week 4: Validity in Design and Analysis
Week 5: One-Factor Between-Subjects Experiments
Week 6: One-Factor Within-Subjects Experiments
Week 7: Factorial Experiment Designs
Week 8: Generalizing the Response
Week 9: The Power of Mixed Effects Models
Meet the instructors
Scott Klemmer
Professor
Cognitive Science & Computer Science
Jacob O. Wobbrock
Professor
The Information School