ST370 - Probability and Statistics for Engineers
- Prerequisites: MA 241
- Term & Frequency: Fall and Spring
- Student Audience: Sophomores, juniors and seniors in engineering disciplines
- Credit: 3 Credits
- Recent Texts: L. Lapin: Modern Engineering Statistics, first ed., 1997, Duxbury Press, by L. Lapin; Applied Statistics and Probability for engineers, John Wiley & Sons, Inc, by D. C. Montgomery, G. C. Runger
- Recent Instructors: Charlie Smith, Justin Post, Jonathan Duggins, Herle McGowan, Donald Martin, Brooke Alhanti
- Background and Goals: Calculus-based introduction to probability and statistics with emphasis on the study being able to gather and analyze data for a two or higher factor designed experiment as a final project. The Anova and multiple regression analysis is done using either Matlab, R, JMP, or Stat-crunch. Statistical methods include point and interval estimation of population parameters and curve and surface fitting (regression analysis). The principles of experimental design and statistical process control introduced.
- Content: The course is divided into 8 units: Collection and Analysis of Data, Experimental Design and Factorial Experiments with ANOVA, Simple and Multiple Regression, Probability, Random Variables, Random Samples and the Central Limit Theorem, Estimators and Confidence Intervals, Hypothesis Testing.
- Alternatives: ST371-372
- Subsequent Courses: None
S1 2017 Sections:
|001||Alhanti,Brooke ||01216 SAS Hall||09:50AM-11:20AM||MTWThF||23/50 - Open|
|301|| ||TBA|| - ||TBA||0/100 - Closed|