ISEN 2610 02: Engineering Statistics

ISEN 2610 - Engineering Statistics

Fall 2026 Syllabus, Section 02, CRN 44238,

Credit hours: 3

Course Meeting Times

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Instructor

Zefeng Lyu

Email: zlyu@ysu.edu

Public Instructor Information

Instructor Title: Assistant Professor
Instructor Professional Qualifications: Ph.D., Industrial Engineering, University of Tennessee, 2023
Instructor Office Location: Moser Hall 2442
Instructor Office Phone: (330) 941-7455

Private Instructor Information

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Course Description

2610. Engineering Statistics. Applications of data collection and analysis techniques to engineering problems. Techniques for data structuring, data modeling, parameter estimation, and design of experiments utilizing engineering data. Prereq.:C or better in one of MATH 1570 or MATH 1571 or MATH 1571H or MATH 1585H, C or better in either ENGR 1550 or ENGR 1550H. 3 s.h.

Course Readings

Group Title Author ISBN
Optional An Introduction to Statistical Methods and Data Analysis R. Lyman Ott and Michael Longnecker 1305269470
Optional Engineering Statistics Montgomery, Runger, Hubele 0470631473 All course
 
 
 

The course readings are subject to change in the event of extenuating circumstances, research developments, current events, and/or to ensure better learning.  

Additional Course Materials

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Course Learning Outcomes/Objectives/Goals

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How to Succeed in This Course

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Attendance Expectations

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Late Work Submission Policy

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Additional Course Expectations

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Artificial Intelligence Policy Statement

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Assignments/Assessments

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Grading and Grading Scale

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University Policies

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Schedule of Topics and Assignments

Week of Proposed Topic Due/To Prepare for Class
8/24 Probability concept
Computing probability
8/31 Random variables - discrete
Bayes rule
9/7 Random variables – continuous
Jointly distributed random variables
9/14 Data description – measures of central tendency
Data description – measures of variability
9/21 Box plots
9/28 Sample distribution of the mean
Central limit theorem
10/5 Introduction to inferences
Confidence interval for the binomial parameter
10/12 Inference for the population mean
t-distribution
Confidence interval for population mean
10/19 Null and alternative hypothesis
Choosing the hypothesis
10/26 The nature of hypothesis testing
11/2 Introduction to comparing two population means
Comparing two population means: paired data
Comparing two population means: independent samples
11/9 Comparing two population proportions with independent samples
Contingency tables and Chi-square test of independence
11/16 Simple Linear Regression
11/23 Correlation coefficient and coefficient determination
11/30 Simple linear regression for forecasting

The course schedule, policies, procedures, and assignments in this course are subject to change in the event of extenuating circumstances, by mutual agreement, and/or to ensure better learning.