Subject: Subject Sylbus: The Human Factor in Data Collection - 096275

The Human Factor in Data Collection - 096275
Given In
  Lecture Exercise Laboratory Project or
2 1 1 1  

Determination of the grade according to progress during the semester and a final examination.

Prerequisites: Machine Learning 1 096411
or ( Introductio to Data Science 094201
and Introduction to Statistics 094423 )
or ( Introduction to Statistics 094423
and Introduction to Data Science and Engin. 094700 )
Overlapping Courses: Introduction to Human Factors Engineering 096620
Incorporated Courses: Introduction to Man-Machine Systems 094140
Human Performance 095618

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.

System of hours to the semesters
Semester Previous Semester information 01/2020 2020/2021 Winter Semester

2017princeton, nj: princeton university presssalganik, matthew review edition: bit by bit: social research

Created in 22/04/2021 Time 15:25:46