STEMskiller: Skill Set Map for Mentors of Early Career Researchers

RESEARCH AND SCHOLARSHIP: Academic reading and writing

[Writing specifics for different academic formats] [Research articles] [Valid scientific argumentation]

Quantitative statistics


For quantitative research, mentees must be able to understand probability and statistics concepts as well as be able to understand and interpret basic statistical data/representations thereof.  

Useful resources on Quantitative statistics:

Carpi, A., & Egger, A. E. (2008). Statistics in Science.

Concise overview article that discusses current use of statistics in science and includes a quiz and links to additional reading. Includes: What is statistics; statistics in research design; statistics in data analysis; and limitations, misconceptions, and the misuse of statistics.

Poldrack, R. A. (2019). Statistical Thinking for the 21st Century. _Statistics/Book%3A_Statistical

Textbook including: introduction, working with data, introduction to R, summarizing data, summarizing data with R (with Lucy King), data visualization, data visualization with R (with Anna Khazenzon), fitting models to data, fitting simple models with R, probability, probability in R (with Lucy King), sampling, sampling in R (with Lucy King), resampling and simulation, resampling and simulation in R, hypothesis testing, hypothesis testing in R, quantifying effects and designing studies, statistical power in R, Bayesian statistics, Bayesian statistics in R, modeling categorical relationships, modeling categorical relationships in R, modeling continuous relationships, modeling continuous relationships in R, the general linear model, the general linear model in R, comparing means, comparing means in R, practical statistical modeling, practical statistical modeling in R, and doing reproducible research.

Shafer & Zhang. (2019). Introductory Statistics.

Textbook including: introduction to statistics, descriptive statistics, basic concepts of probability, discrete random variables, continuous random variables, sampling distributions, estimation, testing hypotheses, two-sample problems, correlation and regression, and chi-square tests and f-tests.

Tags: IPS IA; IPS QL; IPS PS; IAL IntL; CompQ; CompTS

Peer Review: None

Table of contents:


Author: Stephanie Krueger

Peer Reviewer(s): None

Last Updated: October 22, 2021


Editor: Stephanie Krueger Last modified: 22.10. 2021 15:10