STAT 201
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Statistics for Engineers and Scientists
StatisticsCollege of Computational, Mathematical, & Physical Sciences
Course Description
Explores statistics through observational studies, experiments, probability, inference, and data analysis. Emphasizes variability, modeling, and software tools to solve scientific and engineering problems, and support evidence-based decision making.
When Taught
Fall, Winter, Spring
Min
3
Fixed/Max
3
Fixed
3
Fixed
0
Prerequisite
Complete ANY of the following Courses:
- 03615-008
OR 03616-004
Recommended
Prior Python programming experience
Title
Understand and apply foundational statistical principles
Learning Outcome
Explain and implement core concepts of descriptive statistics, probability, sampling distributions, and statistical inference, including confidence intervals, hypothesis testing, and basic linear models.
Title
Design and critique data collection strategies
Learning Outcome
Distinguish appropriate principles of experimental design and sampling methods, evaluate bias, and distinguish between observational and experimental studies.
Title
Model and analyze data using computational tools
Learning Outcome
Use statistical software to summarize, visualize, and analyze data using appropriate models for both discrete and continuous random variables.
Title
Draw valid conclusions and communicate results clearly
Learning Outcome
Interpret results of statistical analyses, assess practical significance, and effectively communicate findings.
Title
Make evidence-based decisions in engineering contexts
Learning Outcome
Apply statistical methods to real-world engineering problems, recognizing the limitations of inference.
Title
Evaluate ethical and moral dimensions of data usage
Learning Outcome
Demonstrate integrity in data analysis, avoid misuse of statistics, and thoughtfully engage with ethical questions surrounding uncertainty, fairness, and decision-making.
Title
Foster curiosity and prepare for lifelong learning
Learning Outcome
Develop confidence and curiosity in approaching data-driven problems, laying a foundation for further study in science, engineering, and interdisciplinary applications.
