Introduces the tools of statistical analysis. Combines theory with extensive data collection and computer-assisted laboratory work. Develops an attitude of mind accepting uncertainty and variability as part of problem analysis and decision-making. Topics include: exploratory data analysis and data transformation, hypothesis-testing and the analysis of variance, simple and multiple regression with residual and influence analyses.
Course Master:
Term:
Spring 2025
Discipline:
DS (Data Science)
Credits:
4 credits
Type:
CCM
Level:
Undergraduate
Can be taken twice for credit?:
No
Cross Listed:
Exam Date:
Monday, May 12, 2025 - 09:00
Pre-requisites:
MA0900 OR MA1005 OR MA1005CCM OR MA1005GE120 OR ELECMA-25 OR ELECMA-20 OR ELECMA-30 OR (MA1025CCM OR MA1025GE120) OR MA1030 OR MA1030CCM OR MA1030GE120 OR MA1091 OR MA1091CCM OR MA1091GE120
Co-requisites:
None
