Designing, Running, and Analyzing Experiments
€0, aangeboden door Coursera
About this course: You will never know whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design experiments, how to run 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 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. By the end of the course, you will be able to knowledgeably design, run, and analyze your own experiments for putting empirical and statistical weight behind your designs.
Created by:Â Â Â University of California, San Diego
Taught by:Â Â Â Â Scott Klemmer, Associate Professor
Cognitive Science & Computer Science
Taught by:Â Â Â Â Jacob O. Wobbrock, Associate Professor
The Information School
Basic Info
Course 7 of 8 in the Interaction Design Specialization.
Commitment
9 weeks, 2-3 hours/week
Language
English
How To Pass
Pass all graded assignments to complete the course.
User Ratings
3.4 stars
Average User Rating 3.4See all 32 reviews
Course 7 of Specialization
Learn how to design great user experiences. Design that delights users
Interaction Design
University of California, San Diego
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Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
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About 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.
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...Â
2 videos, 1 reading
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Graded: Understanding the Basics
WEEK 2
User Preferences: 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...Â
7 videos
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Graded: Understanding Tests of Proportions
WEEK 3
Website A/B Tests: 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...Â
2 videos
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Graded: Understanding Experiment Designs
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...Â
4 videos
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Graded: Understanding Validity
WEEK 5
Task Completion in Authoring Tools: 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...Â
3 videos
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Graded: Understanding Oneway Designs
WEEK 6
Human Search Performance: 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...Â
5 videos
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Graded: Understanding Oneway Repeated Measures Designs
WEEK 7
Smartphone Text Entry: 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, ...Â
4 videos
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Graded: Understanding Factorial Designs
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...Â
2 videos
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Graded: Understanding 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...Â
4 videos
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Graded: Understanding Mixed Effects Models