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Dec 15, 2025
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ISE 6120 - Probabilistic System Analysis Intended to prepare engineering management students to design statistically valid experiments and to analyze the results of those experiments to draw conclusions about a population. Analysis methods covered include hypothesis testing and regression.
Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: - Compare two populations, for both mean and variation, using random samples.
- Conduct hypothesis tests on population parameters utilizing point estimates from random samples.
- Describe an unknown population using statistics from a random sample.
- Describe the parameters and the application of common sampling distributions.
- Determine sample sizes for hypothesis tests of population means.
- Determine the best sample measure of central tendency and variation for a sample from a known population distribution.
- Plot X, Y data and identify linear and transformable patterns.
- Use ANOVA techniques to identify weak regression models.
- Use ANOVA techniques to test for simple randomized one-factor experiments.
- Use least squares regression methods for single and multiple X variables.
- Use sequential model selection techniques, like stepwise regression, to build prediction models.
- Use tables to calculate probability and its inverse from common distributions.
- Utilize spreadsheet software for basic statistical analysis.
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