APPLIED MATHEMATICS (TURKISH, NON-THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
MAT5018 Statistics I Fall
Spring
3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: Turkish
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. İRİNİ DİMİTRİYADİS
Recommended Optional Program Components: None
Course Objectives: This course provides a sound background on fundemental statistical techniques.

Learning Outcomes

The students who have succeeded in this course;
The student who completes this course will know about the basic notions of probability and statistics, will be able to use moment generating and probability generating functions,will know about basic probability distributions, will be able to fit statistical data to theoretical distributions, will understand interval estimations and interpret hypotheses tests. The student will also be introduced to the basics of linear regression analysis.

Course Content

Collection and tabulation of statistical data, probability, probability distributions, moments and moment generating function, the Normal distribution, approximations, the Central Limit theorem, statistical estimations, interval estimation and hypotheses testing,linear regression analysis.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Statistical data analysis. Collection and graphical portrayal of data. Histograms, quantile plots, box plots.Measures of central tendency, mean, variance and skewness.
2) Review of probability. Definition and properties of random variables, expected value, variance and higher moments.
3) Discrete and continuous probability distributions.Binomial, Poisson, exponential, gamma,Normal and Chi-square distributions.
4) The Normal distribution. Finding areas under the Normal curve, applications and approximations to the Normal. Moments and moment generating and probability generating functions.
5) Sampling distributions. Merkez limit teoremi.
6) Statistical estimation. Properties of point estimators, moment matching and maximum likelihood estimators. Fitting statistical data to theoretical distributions.
7) Confidence intervals, estimation of difference between two means, proportion, variance and ratio of two variances.
8) Tests of Hypotheses. Small and Large sample tests.
9) Tests of hypotheses continued. Types of errors, power of tests.
10) Linear models and estimation by least squares. Simple linear regression.
11) Simple linear regression continued. Application examples.
12) Introduction to multiple linear regression.
13) Multiple linear regression continued.
14) Solution of an extended real life problem.

Sources

Course Notes / Textbooks: Mathematical Statistics with Applications, Mendenhall, Scheaffer, Wackerly, Wadsworth International Student Edition.

Probability and Statistics for Engineers 8th edition Ronald E Walpole.
References:

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 4 % 15
Project 1 % 5
Midterms 2 % 40
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 55
PERCENTAGE OF FINAL WORK % 45
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 3 42
Project 1 16 16
Homework Assignments 4 10 40
Quizzes 4 5 20
Midterms 2 10 20
Final 1 20 20
Total Workload 200

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Ability to assimilate mathematic related concepts and associate these concepts with each other.
2) Ability to gain qualifications based on basic mathematical skills, problem solving, reasoning, association and generalization.
3) Be able to organize events, for the development of critical and creative thinking and problem solving skills, by using appropriate methods and techniques.
4) Ability to make individual and team work on issues related to working and social life.
5) Ability to transfer ideas and suggestions, related to topics about his/her field of interest, written and verball.
6) Ability to use mathematical knowledge in technology.
7) To apply mathematical principles to real world problems.
8) Ability to use the approaches and knowledge of other disciplines in Mathematics.
9) Be able to set up and develope a solution method for a problem in mathematics independently, be able to solve and evaluate the results and to apply them if necessary.
10) To apply mathematical principles to real world problems.
11) To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively.
12) To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself.