| Course Type | Elective Course |
|---|
| Course Level | Master's Degree Without Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- To be able to define basic concepts related to statistics
- Be able to distinguish between data types
- To be able to compute descriptive statistics used to summarize data set
- To be able to define basic concepts about probability
- To make basic probability calculations
- To be able to calculate the probabilities by probability functions of discrete and continuous random variables
- To be able to calculate mathematical Expected Value
- To be able to obtain the moments of the random variable
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | No |
|---|
| Course Description | To introduce; fundemantal elements of Statistics and Probability, graphical and numerical methods for describing data sets, how to calculate probability, how to form probability distributions for both discrete and continuous random variables and how to calculate mathematical expectation. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
The Science of Statistics, Types of Statistical Applications, Fundemantal Elements of Statistics |
|
2nd Week |
Types of Data, Collecting Data |
|
3rd Week |
Describing Qualitative Data, Graphical Methods for Describing Quantitative Data |
|
4th Week |
Numerical Measures for Central Tendency |
|
5th Week |
Numerical Measures for Variability, Numerical measures for Relative Standing |
|
6th Week |
Combinatorial Methods |
|
7th Week |
Sample Spaces and Events, Unions and Intersections, Complementary Events, Additive Rule and Mutually Exclusive Events |
|
8th Week |
Midterm Exam |
|
9th Week |
The Probability of an Event, Some Rules of Probability, Conditional Probability, |
|
10th Week |
Independent Events and The Multiplicative Rule, Bayes Theore |
|
11th Week |
Discrete Random Variables, Probability Distributions |
|
12th Week |
Continuous Random Variables, Probability Density Functions |
|
13th Week |
The Expected Value of Random Variable |
|
14th Week |
Moments |
|
| Recommended or Required Reading | Materials to be used for the course will be provided by the course the teachers. |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Practice
- Questions/Answers
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Assignment |
1 |
15 |
| Quiz |
1 |
20 |
| Total(%) |
|
65 |
| Contribution of In-term Studies to Overall Grade(%) |
|
65 |
| Contribution of Final Examination to Overall Grade(%) |
|
35 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
1.67 |
1.67 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
3 |
42 |
| Preparation for Final exam |
1 |
50 |
50 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
50 |
50 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
1.67 |
1.67 |
| Homework |
2 |
50 |
100 |
| Total Work Load | 287.34 |
| Total Work Load / 30 (h) | 9.57 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
