Syllabus ( MATH 118 )
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Basic information
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| Course title: |
Probability and Statistics |
| Course code: |
MATH 118 |
| Lecturer: |
Assist. Prof. Hadi ALIZADEH
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| ECTS credits: |
6 |
| GTU credits: |
3 (3+0+0) |
| Year, Semester: |
1, Spring |
| Level of course: |
First Cycle (Undergraduate) |
| Type of course: |
Compulsory
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| Language of instruction: |
Turkish
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| Mode of delivery: |
Face to face
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| Pre- and co-requisites: |
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. |
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Learning outcomes
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Upon successful completion of this course, students will be able to:
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Apply the fundamental concepts of probability and statistics to real-world engineering problems.
Contribution to Program Outcomes
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Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
Method of assessment
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Written exam
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Homework assignment
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Construct the probability distributions of random variables based on real-life scientific scenarios and data sets, and then use it to find expectation and variance.
Contribution to Program Outcomes
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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.
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Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
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Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
Method of assessment
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Written exam
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Homework assignment
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Explain the fundamental concepts of probability theory.
Contribution to Program Outcomes
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Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
Method of assessment
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Written exam
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Contents
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| 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 |
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* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
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Assessment
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| Method of assessment |
Week number |
Weight (%) |
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| Mid-terms: |
9 |
30 |
| Other in-term 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 |
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Total weight: |
(%) |
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Workload
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| Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
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| Courses (Face-to-face teaching): |
3 |
14 |
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| Own studies outside class: |
2 |
14 |
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| Practice, Recitation: |
0 |
0 |
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| Homework: |
2 |
13 |
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| Term project: |
0 |
0 |
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| Term project presentation: |
0 |
0 |
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| Quiz: |
0 |
0 |
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| Own study for mid-term exam: |
10 |
1 |
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| Mid-term: |
2 |
1 |
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| Personal studies for final exam: |
10 |
1 |
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| Final exam: |
2 |
1 |
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Total workload: |
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Total ECTS credits: |
* |
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* ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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