STEMskiller: Skill Set Map for Mentors of Early Career Researchers
Data analysis: concepts and definitions, resources for learning more
Many early career researchers work with data generated in the course of a research project and have familiarity with specific quantitative data analysis tools (e.g., R), but making sense of what conclusions can be drawn from data gathered and understanding whether or not conclusions can be made in the quantitative or qualitative sense fall into the realm of data analysis.
Useful resources on Data analysis:
George Mason University Libraries. (2020). Intro to data analysis and statistics. https://infoguides.gmu.edu/statsclass/concepts
Links to high-quality educational content (including exercises and videos) for understanding Measurements and Distributions (Probability Distributions, Z-Scores; Sampling Distribution, Standard Error; Estimation, Confidence Intervals) and Hypothesis Testing (Null Hypothesis Significance Testing & P-Values, Topics in Statistical Analysis, Power & Error).
Pelz, B. (n.d.). Research methods for the social sciences. https://courses.lumenlearning.com/suny-hccc-research-methods/
Open course intended for introducing students to the concept of research together with quantitative and qualitative research methods. Includes open textbook, learning modules, and assignments.
Wikipedia. (2020). Data analysis. https://en.wikipedia.org/wiki/Data_analysis
Introductory definition of data analysis with descriptions of difference aspects of the data analysis process. Suitable for providing students with an overview of the complexity of this topic, including barriers to effective analysis such as bias.
Tags: IPS QL; Comp; CompGS
Peer Review: None
Table of contents:
- 1.6. Research data
- 1.6.3. Presenting data
- 1.6.4. Storing data
Author: Stephanie Krueger
Peer Reviewer(s): None
Last Updated: October 26, 2021