STEMskiller: Skill Set Map for Mentors of Early Career Researchers

RESEARCH AND SCHOLARSHIP: Research data

[Working with data]

Data analysis: concepts and definitions, resources for learning more

Definition:

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

1.6.1. Data gathering and organizing

1.6.2. Working with data (modeling, simulation, analysis)

1.6.2.2. Advanced techniques in modelling complex systems
1.6.2.3. Information processing and exchange
1.6.2.4. Using R for statistical data analysis
1.6.2.5. Programming/coding basics
1.6.2.6. Software usage and development
1.6.2.7. Sensitive data

1.6.3. Presenting data

1.6.4. Storing data

Author: Stephanie Krueger

Peer Reviewer(s): None

Last Updated: October 26, 2021