Survey Data Collection and Analytics 专项课程

于 Oct 16 开始

Survey Data Collection and Analytics 专项课程

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

本专项课程介绍

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.

制作方:

courses
7 courses

按照建议的顺序或选择您自己的顺序。

projects
项目

旨在帮助您实践和应用所学到的技能。

certificates
证书

在您的简历和领英中展示您的新技能。

课程
Beginner Specialization.
No prior experience required.
  1. 第 1 门课程

    Framework for Data Collection and Analysis

    课程学习时间
    4 weeks of study, 1-2 hours/week
    字幕
    English

    课程概述

    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 question
  2. 第 2 门课程

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

    课程学习时间
    4 weeks of study, 2-4 hours/weeks
    字幕
    English

    课程概述

    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 and
  3. 第 3 门课程

    社会调查的问卷设计

    课程学习时间
    4-8小时/周
    字幕
    English

    课程概述

    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 quest
  4. 第 4 门课程

    Sampling People, Networks and Records

    字幕
    English

    课程概述

    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
  5. 第 5 门课程

    Dealing With Missing Data

    课程学习时间
    学习时长:4周,每周时间1-2小时
    字幕
    English

    课程概述

    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 propensi
  6. 第 6 门课程

    Combining and Analyzing Complex Data

    字幕
    English

    课程概述

    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 co
  7. 第 7 门课程

    Survey Data Collection and Analytics Project (Capstone)

    计划开课班次:Nov 26
    字幕
    English

    毕业项目介绍

    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 criti

制作方

  • 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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