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Oct 10, 2024
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ET 2450 - Engineering Statistics This course covers engineering statistics with a goal to prepare engineering and technology students to design statistically valid experiments and to analyze the results of those experiments to draw conclusions. Topics include functions of random variables, fundamentals of probability theory, sampling distributions, probability density function and cumulative distribution function, estimation theory, hypothesis testing, statistical prediction, ANOVA techniques, simple linear regression analysis, and computer software for basic statistical analysis.
Requisites: MATH 2301 and WARNING: no credit if taken after GEOL3050, GEOG2710, ISE3040, ISE3200, ET2400, PSY1110, MATH2500, QBA2010, ECON3810 Credit Hours: 3 OHIO BRICKS Arch: Constructed World Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Course Transferability: OTM course: TMMSL Transfer Module Mathematics, Statistics and Logic College Credit Plus: Level 1 Learning Outcomes: - Students will be able to identify discrete and continuous random variables and use descriptive statistics.
- Students will be able to calculate probabilities, conditional probabilities, permutations and combinations.
- Students will be able to conduct hypothesis tests and calculate confidence intervals on population parameters using point estimates from random samples (mean, variance, proportion).
- Students will be able to use Analysis of Variance (ANOVA) techniques to test for simple randomized one-factor experiments.
- Students will be able to perform simple linear regression and evaluate the strength and significance of the relationship between X and Y.
- Students will be able to utilize quantitative analyses for engineering solutions in order to develop statements for the support of decision-making processes and dissemination to a variety of audiences.
- Students will be able to state conclusions and related outcomes based on statistical tests (consequences and implications) logically and in a priority order.
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