The Human Factor in Data Collection - 096275
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Lecture |
Exercise |
Laboratory |
Project or
Seminar |
House
Work |
Weekly
Hours |
2 |
1 |
1 |
1 |
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Determination of the grade according to progress during the semester and a final examination.
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Prerequisites:
| | | | Machine Learning 1 |
096411
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or
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(
| | Introductio to Data Science |
094201
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and
| Introduction to Statistics |
094423
| ) |
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or
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(
| | Introduction to Statistics |
094423
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and
| Introduction to Data Science and Engin. |
094700
| ) |
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Overlapping Courses:
| | | | Introduction to Human Factors Engineering |
096620
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Incorporated Courses:
| | | | Introduction to Man-Machine Systems |
094140
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| | | | Human Performance |
095618
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The Acquisition of Principles and Considerations in Gathering Data from People, with Emphasis on Considerations from the Point of View of the Respondent, Including Cognitive Abilities and Limitations That Influence the Design of the Tasks and the Motivation to Provide Responses and Ethical Issues. Design Quality Checks for Data. the Course Covers Content from Psychology, Human Factors Engineering, Marketing, and Analysis of Big Data. Lerning Outcomes: at the End of the Course the Student Will:
1. Know Methods for Collecting Big Data from People
2. Understand the Limitations of Human Cognition in Providing Required Data
3. Know How to Choose a Target Audience to Avoid Bias in Data Collection.
4. Understand Ethical Issues in Data Collection.
Textbooks| Published | Publisher | Authors | Book |
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| 2017 | princeton, nj: princeton university press | salganik, matthew j. | open review edition: bit by bit: social research |
Created in 08/03/2021 Time 15:18:41
