This course is designed to improve your data science skills by introducing you to advanced statistical techniques that have become increasingly important in psychology and a variety of fields. The focus will be on understanding the advantages and limitations of regression approaches and multivariate analytic techniques that permit simultaneous prediction of multiple outcomes. Topics covered will include basic regression approaches, advanced regression strategies, structural equation modeling, factor analysis, measurement models, path modeling, modeling of longitudinal data sets, multilevel modeling approaches and growth curve modeling. Students will gain familiarity with these techniques by working with actual data sets. The last part of each class will be reserved for lab time to apply lessons from class to an assignment due the following week. Students are welcome to stay beyond the noon ending time to complete the assignment. Prerequisites: Required: PSYC Research Methods and Statistics 205 (BMC), Psych 200 (HC) Experimental Methods and Statistics, or BIOL B215 Experimental Design and Statistics. Students with good statistical preparation in math or other disciplines and some knowledge of core methods used in social science or health-related research should consult with the instructor to gain permission to take the class.This course was formerly numbered PSYC B314; students who previously completed PSYC B314 may not repeat this course.
- Subject
- DSCI B
- Credits (min)
- 1
- Credits (max)
- 1
- Credit unit
- Credit
- Type
- course
- Edition
- 2026-2027
- Catalog
- Catalog 2026-2027
- Source
- catalog.haverford.edu