EPOKA UNIVERSITY
FACULTY OF ARCHITECTURE AND ENGINEERING
DEPARTMENT OF CIVIL ENGINEERING
COURSE SYLLABUS
2025-2026 ACADEMIC YEAR
COURSE INFORMATIONCourse Title: PROBABILITY AND STATISTICS FOR ENGINEERS |
| Code | Course Type | Regular Semester | Theory | Practice | Lab | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| MTH 205 | A | 3 | 2 | 2 | 0 | 3 | 5 |
| Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature) | Assoc.Prof.Dr. Mirjam Ndini mndini@epoka.edu.al |
| Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours: | Assoc.Prof.Dr. Mirjam Ndini mndini@epoka.edu.al , 8:30-17:30 |
| Second Course Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours: | NA |
| Language: | English |
| Compulsory/Elective: | Compulsory |
| Study program: (the study for which this course is offered) | Bachelor in Civil Engineering (3 years) |
| Classroom and Meeting Time: | Wednesday: 13:40-16:30 |
| Teaching Assistant(s) and Office Hours: | NA |
| Code of Ethics: |
Code of Ethics of EPOKA University Regulation of EPOKA University "On Student Discipline" |
| Attendance Requirement: | |
| Course Description: | This course provides an elementary introduction to probability and statistics with applications. Descriptive statistics. Sets, events, and probability. Concept and definition of random variables and different functions of random variables. Both univariate and multivariate functions will be discussed. Discrete (binomial distribution, Poisson’s distribution) and continuous distribution functions (normal, lognormal, exponential distribution, gamma distribution), with the focus to commonly used probability distribution functions in civil engineering. Statistical estimation and testing; confidence intervals; and an introduction to linear regression. Statistics of extreme events. Testing of hypothesis. Engineering application. |
| Course Objectives: | The objective of a "Probability and Statistics for Engineers" course is to equip students with the necessary tools to model, analyze, and make data-driven decisions while solving engineering problems. The course focuses on applying foundational statistical and probabilistic theory to real-world engineering challenges, where variability and uncertainty are common factors. |
|
BASIC CONCEPTS OF THE COURSE
|
| 1 | Population and sample; |
| 2 | Parameter and statistic; |
| 3 | Descriptive statistics; Measures of central tendency; Measures of dispersion; |
| 4 | Inferential statistics: Hypothesis testing; Confidence intervals |
| 5 | Central Limit Theorem: |
| 6 | Data visualization |
|
COURSE OUTLINE
|
| Week | Topics |
| 1 | Course Introduction. Introduction to Statistics. The population and sample. |
| 2 | Descriptive Statistics-Graphical Methods |
| 3 | Descriptive Statistics- Numerical Methods |
| 4 | Probability |
| 5 | Quiz-1. Discrete Random Variables and Their Probability Distributions |
| 6 | Probability and probability Distribution ; conditional probability and the multiplication rule Rule EventsMathematical Expectation. Mean, Variance of RV. |
| 7 | SEVERAL USEFUL DISCRETE DISTRIBUTIONS |
| 8 | Midterm exam. |
| 9 | Some discrete probability distributions. continue |
| 10 | Continuous Random Variables and Probability Distribution. The normal probability distribution |
| 11 | Quiz 2. Sampling Distribution . Statistics and Sampling Distributions. The Central limit Theorem |
| 12 | One and t wo sample tests of hypotheses. Hypothesis testing. |
| 13 | Simple linear regression and correlation |
| 14 | Review. |
| Prerequisite(s): | Calculus I, II |
| Textbook(s): | 1. Introduction to Probability and Statistics. William Mendenhall, III Robert J. Beaver University of California, Riverside, Emeritus Barbara M. Beaver University of California, Riverside, Emeritus 2. Probability & Statistics for Engineers & Scientists N I N T H E D I T I O N Ronald E. Walpole- Roanoke College; Raymond H. Myers- Virginia Tech; Sharon L. Myers-Radford University; Keying Ye -University of Texas at San Antonio http://fac.ksu.edu.sa/sites/default/files/probability_and_statistics_for_engineers_and_scient isst.pdf |
| Additional Literature: | |
| Laboratory Work: | |
| Computer Usage: | Excel statistical software |
| Others: | No |
|
COURSE LEARNING OUTCOMES
|
| 1 | Establish a foundation in probability: Introduce students to basic probability theory, including concepts such as conditional probability, random variables, and key distributions (e.g., normal, binomial, Poisson). |
| 2 | Develop an understanding of statistical methods: Familiarize students with descriptive and inferential statistics. This includes techniques for summarizing data, estimating population parameters from samples, constructing confidence intervals, and testing statistical hypotheses. Student should be able to organize and manipulate data, derive statistical distribution, and have the ability to translate to information. Have knowledge of statisticsUse statistical methodology and tools in the engineering problem-solving process. |
| 3 | Compute and interpret descriptive statistics using numerical and graphical techniques. |
| 4 | Apply concepts to engineering challenges: Demonstrate how statistical methods are used to solve practical engineering problems in areas like quality control, reliability analysis, and design optimization. Foster data-driven decision-making: Train students to use data analysis to make informed, objective choices in their engineering practice, rather than relying on guesswork. |
| 5 | Solve basic problems arising in engineering that involve discrete and continuous probability distributions. The students will understand central tendency and variability. |
| 6 | The students will be able to understand confidence intervals and perform statistical inference such as hypothesis testing and regression. |
| 7 | The students will be able to carry out error analysis. Compute point estimation of parameters, explain sampling distributions, and understand the central limit theorem. |
| 8 | Understand the basic concepts of probability, random variables, probability distribution, and joint probability distribution. |
| 9 | |
| 10 |
|
COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES
(Blank : no contribution, 1: least contribution ... 5: highest contribution) |
| No | Program Competencies | Cont. |
| Bachelor in Civil Engineering (3 years) Program | ||
|
COURSE EVALUATION METHOD
|
| Method | Quantity | Percentage |
| Homework |
4
|
5
|
| Midterm Exam(s) |
1
|
30
|
| Quiz |
2
|
10
|
| Final Exam |
1
|
30
|
| Total Percent: | 100% |
|
ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)
|
| Activities | Quantity | Duration(Hours) | Total Workload(Hours) |
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 4 | 64 |
| Mid-terms | 1 | 1 | 1 |
| Assignments | 0 | ||
| Final examination | 1 | 2 | 2 |
| Other | 2 | 5 | 10 |
|
Total Work Load:
|
125 | ||
|
Total Work Load/25(h):
|
5 | ||
|
ECTS Credit of the Course:
|
5 | ||
|
CONCLUDING REMARKS BY THE COURSE LECTURER
|
|
Course communication: Discussion during classes. Office hours at A-211. E-mail for questions regarding course: mndini@epoka.edu.al (Ensure that CE 341 is in the subject line. Failure to do so may result in a non-response.) All members of the class are expected to follow rules of common courtesy in all classroom discussions, email messages, threaded discussion and chats. |