Republic of the Philippines
CEBUTECHNOLOGICAL UNIVERSITY
TUBURAN CAMPUS
Brgy 8, PoblacionTuburan, Cebu, Philippines
Website: http://www.ctu.edu.ph E-mail: tuburan.campus@ctu.edu.ph
Phone: +6332 463 9313 loc. 1526
COURSE SYLLABUS
in
IE PC 213
Statistical Analysis for Industrial Engineering 2
INS Form 1
September 2021
Revision: 5
Page 1 of 7 pages
First Semester, A.Y. 2022-2023
Department/Area
Curriculum
Curricular Year
No. of Hours/Sem
Credit Unit(s)
Prerequisites
:
:
:
:
:
:
COLLEGE OF ENGINEERING
BSIE
SECOND
54
3 Units; 3 hours Lec, 0 hours Lab
IE PC 121 (Statistical Analysis for Industrial Engineering 1)
Vision of the University
Mission of the University
Goals of the University
:
A premier, multidisciplinary-technological university
The University shall primarily provide advanced professional and technical instruction for special purposes, advanced studies in
industrial trade, agriculture, fishery, forestry, aeronautics and land-based programs, arts and sciences, health sciences,
: information technology and other relevant fields of study. It shall also undertake research and extension services and provide
progressive leadership in its areas of specialization ( Sec. 2 of RA 9744).
1. Train and develop students to be future leaders of the society imbued with a sense of social responsibility and environmental
consciousness.
2. Produce globally competent engineering graduates.
:
3. Produce technology-related researches and innovations for the benefit of the society.
4. Provide training and technical know-how to communities for their empowerment, increased livability and sustainability.
Page 2 of 7
Core Values
Program Outcomes
Course Description
Course Learning Outcomes
Commitment, Transparency, Unity, Patriotism, Integrity, Excellence, Spirituality (CTU PIES)
: POa. apply knowledge of mathematics and science to solve complex industrial engineering problems;
POb. design and conduct experiments, as well as to analyze and interpret data;
: The course covers basic concepts in managing the complete flow of materials in a supply chain from suppliers to customers. It
further included the design, planning, execution, monitoring, and control in supply chain management.
:
1. Describe the tools and techniques of statistical design and analyses for industrial engineering applications. (Demonstrating,
POa)
2. Design and conduct valid experiments that statistically analyze and evaluate the results of experiments. (Demonstrating,
POa, POb)
3. Derive conclusions and experiments. (Demonstrating, POa, POb)
Page 3 of 7
Course Content:
INTENDED LEARNING OUTCOMES
(TIME ALLOCATION)
Apply simple linear regression
correlation on problems.
(CO1, CO2)
(12 hours)
ASSESSMENT
TASKS
Problem
Solving
Assignments :
Assignment 1.1
Assignment 1.2
Assignment 1.3
Assignment 1.4
Assignment 1.5
Assignment 1.6
Short quizzes :
Quiz 1 (1.1 & 1.2)
Quiz 2 (1.3 & 1.4)
Quiz 3 (1.5 & 1.6)
Differentiate multiple linear regression
from simple linear regression in
application to problems.
Problem
Solving
Assignments :
Assignment 2.1
TEACHING- LEARNING
ACTIVITIES
CONTENTS
1. Simple linear regression and
Synchronous :
online lecture and
discussion via google
meet
Asynchronous :
Assignments in Google
Classroom
Synchronous :
online lecture and
discussion via google
meet
correlation.
1.1 empirical models
1.2 modelling linear
relationships
1.3 correlation : estimating the
strength of linear relationship
1.4 hypothesis tests in simple
linear regressions
1.5 prediction of new variables
1.6 adequacy of the regression
model
2. Multiple linear regression
2.1 multiple linear regression
model
LEARNING
RESOURCES
Synchronous :
Google Meet
Teacher powerpoint
presentation
Multimedia/Whiteboard
Asynchronous :
Google Drive
Google Classroom
Google (CTU) email
Canvas
Open Educational
Resources
Synchronous :
Google Meet
Teacher powerpoint
presentation
REMARKS
Page 4 of 7
(CO1,CO2)
(12 hours)
Assignment 2.2
Assignment 2.3
Assignment 2.4
Asynchronous :
Assignments in Google
Classroom
Short quizzes :
Quiz 4 (2.1 & 2.2)
Quiz 5 (2.3 & 2.4)
2.2 hypothesis tests in multiple
linear regression
2.3 prediction of new
observations
2.4 model adequacy checking
Multimedia/Whiteboard
Asynchronous :
Google Drive
Google Classroom
Google (CTU) email
Canvas
Open Educational
Resources
Midterm Examination
Analyze designs of single factor
experiments.
(CO2, CO3)
(12 hours)
Problem
Solving
Assignments :
Assignment 3.1
Assignment 3.2
Assignment 3.3
Assignment 3.4
Assignment 3.5
Short quizzes :
Quiz 6 (3.1 & 3.2)
Quiz 7 (3.3 & 3.4)
Quiz 8 (3.5)
Synthesize conclusions on experiments
in the application of various designs,
models, and methods.
(CO2, CO3)
(12 hours)
Problem
Solving
Assignments :
Assignment 4.1
Assignment 4.2
Assignment 4.3
Assignment 4.4
Synchronous :
online lecture and
discussion via google
meet
Asynchronous :
Assignments in google
Classroom
3. Design and analysis of singlefactor experiments
3.1 completely randomized
design3.2 random and fixed
effects experiments
3.3 randomized complete block
design
3.4 latin-square design and
graeco-latin square design
3.5 residual analysis and model
checking
Synchronous :
Google Meet
Teacher powerpoint
presentation
Multimedia/Whiteboard
Asynchronous :
Google Drive
Google Classroom
Google (CTU) email
Canvas
Open Educational
Resources
Synchronous :
online lecture and
discussion via google
meet
Asynchronous :
4. Design of experiments with
several factors
4.1 random mixed models
4.2 general factorial design
4.3 two-factor factorial
experiments
4.4 2nd factorial design
Synchronous :
Google Meet
Teacher powerpoint
presentation
Multimedia/Whiteboard
Page 5 of 7
Assignment 4.5
Assignments in Google
Classroom
4.5 response surface methods
Short quizzes :
Quiz 9 (4.1 & 4.2)
Quiz 10 (4.3, 4.4
Asynchronous :
Google Drive
Google Classroom
Google (CTU) email
Canvas
& 4.5)
Open Educational
Resources
Final Examination
References:
1. Applied statistics and probability for engineers, 5th edition, Douglas C. Montgomery and George C. Runger
2. Introduction to Probability and statistics, 3rd edition, Seldom M. Ross
Course Requirements:
Completion and submission of major examinations, activities, assignments, and quizzes.
Page 6 of 7
Evaluation Procedure:
Grade Component
Attendance
- 10%
Assignments/Activities
- 20%
Quizzes
– 30%
Midterm Exam
Final Exam
PASSING MARK : 50%
Weight
60%
40%
Page 7 of 7
Prepared by:
LOMERA NINAME L. CANAS, IE
San Francisco Campus
DYANNE BRENDALYN MIRASOL-CAVERO, MEIE
Main Campus
Revision Date: August 31, 2022
Submission Date: September 3, 2022
Utilized by: ENGR. LEA MARIE P. RELAVO
Consultation Hours
Contact Details :
:
RITCHIE R. LEQUIGAN , IE , MSME
Daanbantayan Campus
Page 8 of 7
Upon Recommendation of the Curriculum Committee
ENGR. CHRISTINE OMELA V. OCAMPO
Danao Campus
ENGR. AL EMMANUEL L. CABALLES
Tuburan Campus
PROF. FELIXBERTO LUCABON JR.
Daanbantayan Campus
Approved by:
_
DR. CRISTIE ANN L. JACA
University Director for Curriculum and Development
Program Cluster Coordinator