Designing, Running, and Analyzing Experiments

Designing, Running, and Analyzing Experiments

Cours
en
Anglais
90 h
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Source
  • Sur www.coursera.org
Conditions
  • À son rythme
  • Accès libre
  • Certificat payant
Plus d'informations
  • 9 séquences
  • Niveau Intermédiaire

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Détails du cours

Déroulé

  • 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...
  • 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...
  • 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...
  • 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...
  • 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...
  • 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...
  • 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, ...
  • 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...
  • 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...

Prérequis

Aucun.

Intervenants

Scott Klemmer
Professor
Cognitive Science & Computer Science

Jacob O. Wobbrock
Professor
The Information School

Éditeur

L' Université de Californie à San Diego est une université publique de recherche sur les concessions de terres à San Diego, en Californie. Établi en 1960 près de la Scripps Institution of Oceanography préexistante, l'UC San Diego est le plus méridional des dix campus de l' Université de Californie et offre plus de 200 programmes menant à un diplôme de premier cycle et des cycles supérieurs, recrutant 33 096 étudiants de premier cycle et 9 872 étudiants des cycles supérieurs. 

L'UC San Diego est considérée comme l'une des meilleures universités au monde. Plusieurs publications ont classé les départements de sciences biologiques et d'informatique de l'UC San Diego parmi les 10 meilleurs au monde.

Plateforme

Coursera est une entreprise numérique proposant des formations en ligne ouverte à tous fondée par les professeurs d'informatique Andrew Ng et Daphne Koller de l'université Stanford, située à Mountain View, Californie.

Ce qui la différencie le plus des autres plateformes MOOC, c'est qu'elle travaille qu'avec les meilleures universités et organisations mondiales et diffuse leurs contenus sur le web.

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