Sampling People, Networks and Records
date_range Débute le 20 mars 2017
event_note Se termine le 1 mai 2017
list 6 séquences
assignment Niveau : Introductif
label Management et Ressources humaines
chat_bubble_outline Langue : Anglais
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Les infos clés

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En résumé

Good data collection is built on good samples. But the samples can be chosen in many ways. Samples can be haphazard or convenient selections of persons, or records, or networks, or other units, but one questions the quality of such samples, especially what these selection methods mean for drawing good conclusions about a population after data collection and analysis is done. Samples can be more carefully selected based on a researcher’s judgment, but one then questions whether that judgment can be biased by personal factors. Samples can also be draw in statistically rigorous and careful ways, using random selection and control methods to provide sound representation and cost control. It is these last kinds of samples that will be discussed in this course. We will examine simple random sampling that can be used for sampling persons or records, cluster sampling that can be used to sample groups of persons or records or networks, stratification which can be applied to simple random and cluster samples, systematic selection, and stratified multistage samples. The course concludes with a brief overview of how to estimate and summarize the uncertainty of randomized sampling.

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Le programme

  • Week 1 - Module 1: Sampling as a research tool
     
  • Week 2 - Mere randomization
     
  • Week 3 - Saving money using cluster sampling
     
  • Week 4 - Using auxiliary data to be more efficient
     
  • Week 5 - Simplified sampling
     
  • Week 6 - Pulling it all together
     
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Les intervenants

  • James M Lepkowski, Research Professor
    Survey Research Center, Institute for Social Research
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Le concepteur

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
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La plateforme

Coursera est une entreprise numérique proposant des formation 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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