Dec 15, 2025  
OHIO University Graduate Catalog 2019-20 
    
OHIO University Graduate Catalog 2019-20 [Archived Catalog]

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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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