Специализация Survey Data Collection and Analytics

Начинается Aug 27

Специализация Survey Data Collection and Analytics

Collect and analyze data, and communicate results. Learn to collect quality data and conduct insightful data analysis in six courses.

Об этой специализации

This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. In the final Capstone Project, you’ll apply the skills learned throughout the specialization by analyzing and comparing multiple data sources. Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs.

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7 courses

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Проекты

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Курсы
Beginner Specialization.
No prior experience required.
  1. 1-Й КУРС

    Framework for Data Collection and Analysis

    Предстоящая сессия: Aug 27
    Выполнение
    4 weeks of study, 1-2 hours/week
    Субтитры
    English

    О курсе

    This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research questio
  2. 2-Й КУРС

    Data Collection: Online, Telephone and Face-to-face

    Предстоящая сессия: Aug 20
    Выполнение
    4 weeks of study, 2-4 hours/weeks
    Субтитры
    English

    О курсе

    This course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions an
  3. 3-Й КУРС

    Questionnaire Design for Social Surveys

    Предстоящая сессия: Sep 3
    Выполнение
    4-8 hours/week
    Субтитры
    English

    О курсе

    This course will cover the basic elements of designing and evaluating questionnaires. We will review the process of responding to questions, challenges and options for asking questions about behavioral frequencies, practical techniques for evaluating ques
  4. 4-Й КУРС

    Sampling People, Networks and Records

    Предстоящая сессия: Aug 20
    Субтитры
    English

    О курсе

    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, especiall
  5. 5-Й КУРС

    Dealing With Missing Data

    Предстоящая сессия: Aug 20
    Выполнение
    4 weeks of study, 1-2 hours/week
    Субтитры
    English

    О курсе

    This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propens
  6. 6-Й КУРС

    Combining and Analyzing Complex Data

    Предстоящая сессия: Sep 3
    Субтитры
    English

    О курсе

    In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be c
  7. 7-Й КУРС

    Survey Data Collection and Analytics Project (Capstone)

    Предстоящая сессия: Sep 3
    Субтитры
    English

    О дипломном проекте

    The Capstone Project offers qualified learners to the opportunity to apply their knowledge by analyzing and comparing multiple data sources on the same topic. Students will develop a research question, access and analyze relevant data, and crit

Авторы

  • University of Michigan

    Michigan’s academic vigor offers excellence across disciplines and around the globe. The University is recognized as a leader in higher education due to the outstanding quality of its 19 schools and colleges, internationally recognized faculty, and departments with 250 degree programs.

    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.

  • University of Maryland, College Park

    The University of Maryland is a globally recognized leader in entrepreneurship education, and the #1 public university in technology entrepreneurship education.

    The University of Maryland is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of the national academies and scores of Fulbright scholars. The institution has a $1.8 billion operating budget, secures $500 million annually in external research funding and recently completed a $1 billion fundraising campaign.

  • Mariel Leonard

    Mariel Leonard

    Lecturer
  • Frederick Conrad, Ph.D.

    Frederick Conrad, Ph.D.

    Research Professor, Survey Methodology
  • James M Lepkowski

    James M Lepkowski

    Research Professor
  • Frauke Kreuter, Ph.D.

    Frauke Kreuter, Ph.D.

    Professor, Joint Program in Survey Methodology
  • Richard Valliant, Ph.D.

    Richard Valliant, Ph.D.

    Research Professor

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