ISE 315: Engineering Statistics

Term 261 (Fall 2026), Section F03

Instructor: Mansur M. Arief — mansur.arief@kfupm.edu.sa

Department: Industrial and Systems Engineering, College of Computing and Mathematics, KFUPM

Office: Building 22, Room 219

Office hours: Wednesdays, 15:00–16:00, or by appointment

Course Description

Review of estimation. Tests of hypothesis for single and two samples. Applications of tests of hypothesis in engineering. Simple and multiple linear regression and their applications. Design and analysis of single-factor experiments: analysis of variance. Design of experiments with several factors. Case studies in engineering statistics.

Prerequisites

ISE 205 or STAT 319.

Objectives

  1. Present the concepts of tests of hypothesis, regression analysis, and design of experiments.
  2. Demonstrate real applications of design of experiments in engineering.
  3. Perform data analysis, draw valid conclusions, and use these concepts in practice.
  4. Develop students’ skills in using computer technology for statistical analysis.

Course Learning Outcomes

By the end of the course, students will be able to:

  1. Structure engineering decision-making problems as hypothesis tests. (SO-1)
  2. Construct confidence intervals. (SO-1)
  3. Utilize the regression model to estimate the mean response, make predictions, and construct confidence and prediction intervals. (SO-1)
  4. Design and conduct engineering experiments involving several factors using the factorial design approach. (SO-2)

Textbook and References

Reference texts:

Grading

Component Weight
Attendance 5%
Homework 5%
Quizzes 15%
Major Exam 1 25%
Major Exam 2 25%
Final Exam 25%

Attendance is scored out of 5%, with −0.5 for every absence. DN will be enforced upon the 6th unexcused absence.

Exams

Exam Date Coverage
Major Exam 1 October 13, 19:00–21:00 Chapters 7, 8, 9, and 10
Major Exam 2 November 24, 19:00–21:00 Chapters 10, 11, and 12
Final Exam Per the registrar’s announcement Chapters 12, 13, and 14

Course Resources

Course Policy

Honor Code

Students of this course are expected to maintain the highest level of academic integrity and ethics. A KFUPM student does not cheat or tolerate those who do. Every student is expected to submit work that is entirely their own, to properly cite all sources used, and to refrain from any form of academic misconduct.

Plagiarism and Use of Generative AI

Use of another person’s ideas, processes, results, or words requires appropriate credit or reference to the author. Use of generative AI tools is subject to the instructor’s authorization. Submitting the same work in more than one course without the instructor’s permission is not allowed.

Class Attendance

Students are expected to arrive on time for class, consistent with expectations in professional settings. Recording attendance for another student, signing another student’s attendance, or asking another student to record yours will be reported for investigation and may result in severe consequences for both students involved.

Examination Policies

You are expected to adhere to KFUPM policies for all examinations in this course, including quizzes, major exams, midterms, and the final exam. The following policies are enacted in this course during examinations:


This page reflects the official ISE 315 syllabus for Term 261 (v1.1, 19 August 2026). Where any discrepancy arises, the official syllabus distributed on Blackboard applies.