— Statistical Data Science II

Prerequisites & course information

This version has ended; see updated course, below. Course Description: Advanced programming and data manipulation in R. Principles of data visualization. Concepts of correlation, regression, analysis of variance, nonparametrics. Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s). Enrollment Restriction(s): During winter quarter, Pass One restricted to Data Science majors only. Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL); Visual Literacy (VL). STA 035B — Statistical Data Science II (4 units) Course Description: Advanced programming and data manipulation in R. Principles of data visualization. Concepts of correlation, regression, analysis of variance, nonparametrics. Prerequisite(s): ( STA 013 C- or better or STA 013Y C- or better; ECS 032A C- or better or ECS 032AV C- or better) or STA 032 C- or better or STA 035A C- or better or STA 100 C- or better; MAT 016B or MAT 017B (can be concurrent) or MAT 019B (can be concurrent) or MAT 021B (can be concurrent). Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s). Enrollment Restriction(s): Winter quarter, Pass One restricted to Data Science majors only. Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL); Visual Literacy (VL). This course version is effective from, and including: Fall Quarter 2026. Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s). Enrollment Restriction(s): During winter quarter, Pass One restricted to Data Science majors only. Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL); Visual Literacy (VL). STA 035B — Statistical Data Science II (4 units) Course Description: Advanced programming and data manipulation in R. Principles of data visualization. Concepts of correlation, regression, analysis of variance, nonparametrics. Prerequisite(s): ( STA 013 C- or better or STA 013Y C- or better; ECS 032A C- or better or ECS 032AV C- or better) or STA 032 C- or better or STA 035A C- or better or STA 100 C- or better; MAT 016B or MAT 017B (can be concurrent) or MAT 019B (can be concurrent) or MAT 021B (can be concurrent). Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s). Enrollment Restriction(s): Winter quarter, Pass One restricted to Data Science majors only. Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL); Visual Literacy (VL). This course version is effective from, and including: Fall Quarter 2026.