Foundations in Quantitative Analytics for Education and Related Fields

4 credits

Integrates introductory concepts in quantitative analytics with real-world research applications, including measurement scales, sampling distributions (frequentist perspective), null hypothesis significance testing, confidence intervals, and power for 1- and 2-group z/t/chi/F tests, simple linear correlation and regression, and scale reliability and validity (classic test theory). Covers basic coding skills for data analysis and visualization. Recommended: coursework in either pre-algebra or algebra.