Syllabus ( MATH 219 )
|
Basic information
|
|
Course title: |
Probability and Statistics |
Course code: |
MATH 219 |
Lecturer: |
Assist. Prof. Hadi ALIZADEH
|
ECTS credits: |
4 |
GTU credits: |
2 () |
Year, Semester: |
2, Fall |
Level of course: |
First Cycle (Undergraduate) |
Type of course: |
Compulsory
|
Language of instruction: |
English
|
Mode of delivery: |
Face to face
|
Pre- and co-requisites: |
none |
Professional practice: |
No |
Purpose of the course: |
This course is an introduction to probability and statistics. It aims to collect, order, summarize and interpret the data which is related to the subject. In addition it aims to model the data by using various probabilistic calculations. |
|
|
|
Learning outcomes
|
|
Upon successful completion of this course, students will be able to:
-
Analyse the data that collected for any research.
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 real-life problems using mathematical and statistical techniques.
-
Ability to work in interdisciplinary research teams effectively.
-
Adapt to a fast-changing technological environment, improving their knowledge and abilities constantly.
Method of assessment
-
Written exam
-
Make statistical inference by using probability
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 real-life problems using mathematical and statistical techniques.
-
Ability to work in interdisciplinary research teams effectively.
-
Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
Method of assessment
-
Written exam
-
Know the statistical distributions and make modelling.
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.
-
Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
-
Ability to work in interdisciplinary research teams effectively.
Method of assessment
-
Written exam
|
|
Contents
|
|
Week 1: |
Introduction to Probability |
Week 2: |
Basics of Probability |
Week 3: |
Conditional Probability, Bayes Theorem |
Week 4: |
Random Variables, Discrete Random Variables |
Week 5: |
Discrete Distributions |
Week 6: |
Special Discrete Distributions: Bernoulli Experiment, Binomial Distribution, Hypergeometric Distribution |
Week 7: |
Continuous Random Variables |
Week 8: |
Special Continuous Distributions, Midterm Exam. |
Week 9: |
Basic statistical concepts, data, population, sampling |
Week 10: |
Data collecting, Frequency Tables, Graphs |
Week 11: |
Data summarizing, Describing Data with Averages |
Week 12: |
Describing variability: range, variance, standard deviation |
Week 13: |
Relationships: Covariance and Correlation |
Week 14: |
Regression Analysis, Interpretation |
Week 15*: |
- |
Week 16*: |
Final Exam. |
Textbooks and materials: |
• Introduction to Probability and Statistics by Mendenhall, Beaver and Beaver. • A First Course in Probability by Ross S. Prentice Hall Inc. |
Recommended readings: |
• Akdeniz Fikri, Olasılık ve İstatistik, Akademisyen Kitabevi • Schervish M.J. and DeGroot M.H., Probability and Statistics, McGraw Hill |
|
* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
|
|
|
|
Assessment
|
|
|
Method of assessment |
Week number |
Weight (%) |
|
Mid-terms: |
8 |
40 |
Other in-term studies: |
|
0 |
Project: |
|
0 |
Homework: |
|
0 |
Quiz: |
|
0 |
Final exam: |
16 |
60 |
|
Total weight: |
(%) |
|
|
|
Workload
|
|
|
Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
|
Courses (Face-to-face teaching): |
2 |
14 |
|
Own studies outside class: |
2 |
14 |
|
Practice, Recitation: |
0 |
0 |
|
Homework: |
0 |
0 |
|
Term project: |
0 |
0 |
|
Term project presentation: |
0 |
0 |
|
Quiz: |
0 |
0 |
|
Own study for mid-term exam: |
20 |
1 |
|
Mid-term: |
2 |
1 |
|
Personal studies for final exam: |
20 |
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)
|
|
|
-->