Syllabus ( MATH 118 )

Basic information


Course title: 
Probability and Statistics 
Course code: 
MATH 118 
Lecturer: 
Assist. Prof. Hadi ALIZADEH

ECTS credits: 
6 
GTU credits: 
3 (3+0+0) 
Year, Semester: 
1, Spring 
Level of course: 
First Cycle (Undergraduate) 
Type of course: 
Compulsory

Language of instruction: 
Turkish

Mode of delivery: 
Face to face

Pre and corequisites: 
None 
Professional practice: 
No 
Purpose of the course: 
This course will present the fundamental concepts of probability and statistics from an engineering prospective, emphasizing applications. 



Learning outcomes


Upon successful completion of this course, students will be able to:

Apply the fundamental concepts of probability and statistics to realworld engineering problems.
Contribution to Program Outcomes

Describing, formulating, and analyzing reallife problems using mathematical and statistical techniques.
Method of assessment

Written exam

Homework assignment

Construct the probability distributions of random variables based on reallife scientific scenarios and data sets, and then use it to find expectation and variance.
Contribution to Program Outcomes

Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.

Describing, formulating, and analyzing reallife problems using mathematical and statistical techniques.

Having improved abilities in mathematics communications, problemsolving, and brainstorming skills.
Method of assessment

Written exam

Homework assignment

Explain the fundamental concepts of probability theory.
Contribution to Program Outcomes

Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
Method of assessment

Written exam


Contents


Week 1: 
Basic concepts and axioms, sets, counting 
Week 2: 
Permutation and combination 
Week 3: 
Probability 
Week 4: 
Conditional probability, independence 
Week 5: 
Random variables 
Week 6: 
Continuous and discrete random variables 
Week 7: 
Probability distribution functions of random variables 
Week 8: 
Probability density functions of random variables 
Week 9: 
Midterm exam, Gauss, Binomial distributions 
Week 10: 
Binomial, Poisson distributions 
Week 11: 
Geometric and negative binomial distributions 
Week 12: 
Expected value 
Week 13: 
Expected values of random variables 
Week 14: 
Central Limit Theorem 
Week 15*: 
 
Week 16*: 
Final Exam 
Textbooks and materials: 
[1] Probability of Statistics for Engineering & Scientists. Walpole E.W., Myers R.H., Myers S.L., Ye K. Pearson Education, Prentice Hall Inc. 
Recommended readings: 
[1] Probability Random Variables and Stochastic Processes, A.Papolis, McGraw Hill [2] Olasılık, Seymour Lipschutz, Schaum's Outlines 

* Between 15th and 16th weeks is there a free week for students to prepare for final exam.




Assessment



Method of assessment 
Week number 
Weight (%) 

Midterms: 
9 
30 
Other interm studies: 
0 
0 
Project: 
0 
0 
Homework: 
1,2,3,4,5,6,7,8,10,11,12,13,14 
20 
Quiz: 
0 
0 
Final exam: 
16 
50 

Total weight: 
(%) 



Workload



Activity 
Duration (Hours per week) 
Total number of weeks 
Total hours in term 

Courses (Facetoface teaching): 
3 
14 

Own studies outside class: 
2 
14 

Practice, Recitation: 
0 
0 

Homework: 
2 
13 

Term project: 
0 
0 

Term project presentation: 
0 
0 

Quiz: 
0 
0 

Own study for midterm exam: 
10 
1 

Midterm: 
2 
1 

Personal studies for final exam: 
10 
1 

Final exam: 
2 
1 



Total workload: 



Total ECTS credits: 
* 

* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)



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