Course Details

Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
5MATH301PROBABILITY AND STATISTICS3+0+03515.08.2025

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program CIVIL ENGINEERING
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The goal of this course is to familiarize students with powerful analytical and numerical tools in the areas of probability and statistics that can be used to solve real world engineering problems. Lectures will be supplemented by several programming exercises and will include a large number of practical examples. The course content includes basic concepts of probability, probability distributions, Bayes’ theorem, random variables, mean, variance, covariance concepts, basic statistics concepts, confidence interval, hypothesis testing, and linear regression.
Course Content To help students understand of the basic concepts in probability theory and statistical analysis.
To help students understand the fundamental theory of distribution of random variables, the basic theory and techniques of parameter estimation and tests of hypotheses.
To help students perform simple or sophisticated statistical analyses on engineering datasets.
Course Methods and Techniques Lecture, flipped classroom, in-class exercises, programming exercises, projects
Prerequisites and co-requisities ( MATH102 or MATH152 )
Course Coordinator None
Name of Lecturers Research Assist.Dr. Oğuzhan Ayyıldız oguzhan.ayyildiz@agu.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Introduction to Probability, Statistics and Random Processes
Probability & Statistics for Engineers & Statistics, Walpole, Myers, Myers, Ye, 9th Edition, Pearson Publishing
Course Notes (a) Probability & Statistics for Engineers & Statistics, Walpole, Myers, Myers, Ye, 9th Edition, Pearson Publishing

Course Category
Mathematics and Basic Sciences %70
Engineering %30

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Quiz/Küçük Sınav 8 % 60
Ödev 1 % 2
Proje/Çizim 1 % 18
Final examination 1 % 20
Total
11
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Araştırma Ödevi 1 2 2
Yazılı Sınav 1 2 2
Sınıf İçi Aktivitesi 8 16 128
Ders dışı çalışma 2 10 20
Takım/Grup Çalışması 1 5 5
Total Work Load   Number of ECTS Credits 5 157

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Describe basic concepts in probability including combinatorics, independence, conditional probability and Bayes' rule.
2 Apply discrete and continuous probability distribution concepts to solve related problems arising in engineering.
3 Explain statistical concepts such as means, variances and various types of graphs.
4 Perform parameter estimation and statistical inference on the engineering related datasets in a group project.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction, basic concepts Ders notu
2 Probability and conditional probability, Law of total probability
3 Bayes’ theorem
4 Discrete random variables (RVs)
5 Special discrete RV probability distributions
6 Continuous random variables
7 Continuous RV distributions, Joint distributions, Covariance & Correlation
8 Central limit theorem, Law of large numbers
9 Introduction to statistics
10 Confidence interval for one mean, z-interval, t-interval
11 Confidence interval for two means, Welch’s t-Interval, Paired t-Interval
12 Simple linear regression, Least squares method
13 Hypothesis testing: z-test, t-test
14 ANOVA

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
C1 5
C2 5 3 3
C3 5 5
C4 5 5 5 5 3 5 3

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=78654&lang=en