Data Exploration in Psychology
Offered By: American Psychological Association via Coursera
Course Description
Overview
This Specialization is intended to elevate the public’s understanding of, regard for, and use of psychology and strengthen APA’s standing as an authoritative voice for psychology. Specifically, to introduce the use of descriptive statistics in psychological research, including descriptions of how data sets are structured in statistical software, the construction of basic frequency distributions, understanding of measures of central tendency, variability, correlation, and contingency, and the use of statistical software for exploring these descriptive statistics.
Any course can be taken as-is; however, within the specialization, the following order is recommended:
1. How To Create and Explore a Data Set
2. Measures of Central Tendency
3. Measures of Variability
4. Measures of Correlation and Contingency
Syllabus
Course 1: How to Create and Explore a Data Set
- Offered by American Psychological Association. This course provides a comprehensive introduction to data analysis, focusing on the ... Enroll for free.
Course 2: Measures of Central Tendency
- Offered by American Psychological Association. This course provides a comprehensive understanding of central tendency measures, equipping ... Enroll for free.
Course 3: Measures of Variability
- Offered by American Psychological Association. This course provides a comprehensive exploration of statistical variability, equipping ... Enroll for free.
Course 4: Measures of Correlation and Contingency
- Offered by American Psychological Association. This course provides a comprehensive exploration of statistical relationships, focusing on ... Enroll for free.
- Offered by American Psychological Association. This course provides a comprehensive introduction to data analysis, focusing on the ... Enroll for free.
Course 2: Measures of Central Tendency
- Offered by American Psychological Association. This course provides a comprehensive understanding of central tendency measures, equipping ... Enroll for free.
Course 3: Measures of Variability
- Offered by American Psychological Association. This course provides a comprehensive exploration of statistical variability, equipping ... Enroll for free.
Course 4: Measures of Correlation and Contingency
- Offered by American Psychological Association. This course provides a comprehensive exploration of statistical relationships, focusing on ... Enroll for free.
Courses
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This course provides a comprehensive introduction to data analysis, focusing on the understanding and interpretation of data sets. Students will learn to describe data sets, characterize variables, create and interpret graphs, and identify and interpret frequency distributions using jamovi. The course also emphasizes the critical evaluation of data presentation, teaching students to discern the appropriate use and potential misuse of graphs.
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This course provides a comprehensive understanding of central tendency measures, equipping students with the skills to compute, interpret, and distinguish these measures in frequency distributions. It delves into the selection of appropriate measures based on a variable's level of measurement and the shape of its frequency distribution. The course aims to enhance statistical literacy, promoting informed decision-making in various fields.
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This course provides a comprehensive exploration of statistical relationships, focusing on the principles and applications of correlation and contingency tables. Students will learn to identify appropriate scenarios for using correlation, understand its logic, and describe its direction and strength. The course also covers the use of contingency tables, teaching students to recognize patterns of association within them.
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This course provides a comprehensive exploration of statistical variability, equipping students with the skills to identify and interpret various measures within data distributions. Learners will delve into calculating variance and standard deviation, comparing these measures, and understanding their implications. The course also emphasizes graphical analysis, enabling students to visually compare distributions with varying degrees of variability.
Taught by
Mike Stadler, PhD and Peter Cardamone
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