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 data quality in order to sensitize learners to how alternative survey designs might impact the data obtained from those surveys.
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Survey Data Collection and Analytics 専門講座ミシガン大学（University of Michigan）このコースについて
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100%オンライン
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次における7の2コース
初級レベル
約21時間で修了
英語
字幕：フランス語, ポルトガル語（ヨーロッパ）, ロシア語, 英語, スペイン語
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における7の2コース
初級レベル
約21時間で修了
英語
字幕：フランス語, ポルトガル語（ヨーロッパ）, ロシア語, 英語, スペイン語
提供：
ミシガン大学（University of Michigan）
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.
シラバス - 本コースの学習内容
4時間で修了
Module 1: Introduction, Classic Modes of Survey Data Collection
In this lesson, you will be introduced to some key concepts about survey data collection methods that we will rely on throughout the course. By the end of this lesson, you should be well acquainted with the major sources of survey error and how these are affected -- usually in the form of tradeoffs -- by the particular mode used to administer questions and capture responses.
4時間で修了
12件のビデオ （合計134分）, 5 学習用教材, 1 個のテスト
5時間で修了
Module 2: Self-administration, Online Data Collection
This second lesson focuses on modes in which survey respondents self-administer questions and provide their responses directly to researchers. By the end of Lesson 2, you will understand the pros and cons of self-administered modes from the TSE perspective.
5時間で修了
9件のビデオ （合計131分）, 3 学習用教材, 1 個のテスト
6時間で修了
Module 3: Interviewers and Interviewing
In this lesson, we explore the various roles interviewers take on beside asking questions and collecting answers, as well as some of the different approaches to interviewing that have been proposed and how they affect the accuracy of responses. By the end of Lesson 3, you will appreciate the benefits and costs of collecting data in interviews and will be able to contrast them with the costs and benefits of self-administration.
6時間で修了
9件のビデオ （合計173分）, 3 学習用教材, 1 個のテスト
7時間で修了
Module 4: Emerging modes, new data sources
In this lesson, we focus on some new data collection modes such as mobile web surveys and SMS text interviews, as well as alternative data sources such as sensor data, administrative data, and social media. By the end of this lesson, you will have a sense of the issues to which survey methodologists and survey researchers are devoting much of their attention these days. You will be able to weigh the pros and cons of these new methods and data sources.
7時間で修了
12件のビデオ （合計194分）, 5 学習用教材, 2 個のテスト
レビュー
DATA COLLECTION: ONLINE, TELEPHONE AND FACE-TO-FACE からの人気レビュー
Jにより2019年5月26日
- the difference between mobile survey and web survey\n\ndifference between online and face to face interviews\n\ndifference between telephone interviews and computer interviws
SKにより2016年7月19日
There is one word for this Course "Amazing". No matter if you are a undergrad student or a seasoned researcher, you'll feel that you have learned a lot from this course.
EWにより2019年3月27日
Very good summary of the advantages and disadvantages of different approaches to survey data collection, including some useful context about hybrid approaches.
CPにより2017年3月28日
The course material presents the traditional methods and latest developments in data collection for survey research. Excellent overall.
Survey Data Collection and Analytics 専門講座について
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.
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