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: 
20172018 , Fall 
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 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 reallife problems using mathematical and statistical techniques.

Ability to work in interdisciplinary research teams effectively.

Adapt to a fastchanging technological environment, improving their knowledge and abilities constantly.
Method of assessment

Written exam

Homework assignment

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 reallife problems using mathematical and statistical techniques.

Ability to work in interdisciplinary research teams effectively.

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

Written exam

Homework assignment

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: 
Basic statistical concepts, data, population, sampling 
Week 2: 
Data collecting, Frequency Tables, Graphs 
Week 3: 
Data summarizing, Location Parameters 
Week 4: 
Scale Parameters 
Week 5: 
Combination, Permutation, Ordering 
Week 6: 
Probability 
Week 7: 
Random variables, Probability (density) functions 
Week 8: 
Bernouilli, Binom, Geometric and Pascal Distributions 
Week 9: 
Midterm Exam and solutions 
Week 10: 
Poisson Distribution and Normal Distribution 
Week 11: 
Z Table and Central Limit Theorem 
Week 12: 
Other Continious Distributions 
Week 13: 
Regression Analysis, Estimation the coefficients 
Week 14: 
Regression Analysis, Interpretation 
Week 15*: 
 
Week 16*: 
Final Exam 
Textbooks and materials: 
• Probability of Statistics for Engineering & Scientists. Walpole E.W., Myers R.H., Myers S.L., Ye K. Pearson Education, Prentice Hall Inc. • Probability Random Variables and Stochastic Processes, A.Papolis, McGraw Hill

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 (%) 

Midterms: 
9 
30 
Other interm studies: 

0 
Project: 

0 
Homework: 
3, 6, 12, 15 
30 
Quiz: 

0 
Final exam: 
16 
40 

Total weight: 
(%) 



Workload



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

Courses (Facetoface teaching): 
2 
14 

Own studies outside class: 
1 
14 

Practice, Recitation: 
0 
0 

Homework: 
10 
4 

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)



>