| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- will have an ability to interpret statistical data sets by using numerical and graphical techniques.
- will have an ability to learn the probability definition and its rules to be able to solve problems.
- will have an ability to learn the concept of random variables and their probability and distribution functions.
- will have an ability to choose suitable probability distributions to apply and interrelate with the real life problems.
- will have an ability to describe the basic concepts of statistics (population, sample, random sample, sampling distribution etc.)
- will have an ability on using sampling distributions in confidence intervals and sampling distributions, gaining ability of statistical inference.
- will have an ability on determining relationship between variables in research studies.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Topics of statistics and methods, units, mode, population, data analysis, central tendency measurements, sampling and sampling methods, sampling distributions. Estimation of the distribution parameters. Statistical estimation, statistical decision theory and hypothesis tests. Analysis of variance. Regression and correlation analysis. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Probability, random variables and distributions |
|
2nd Week |
Expected value and moments |
|
3rd Week |
Basic discrete distributions |
|
4th Week |
Basic continuous distributions |
|
5th Week |
Random Sampling, Some Important Statistics |
|
6th Week |
Concept of Sampling distribution, Sampling Distributions of Means and S2 |
|
7th Week |
t-Distribution, F-Distribution |
|
8th Week |
Midterm Exam |
|
9th Week |
One- and Two- Sample Hypothesis Testing (for a Variance and the Ratio of Variances), Maximum Likelihood Estimation |
|
10th Week |
Hypothesis Testing, Type I and II Errors. Usage of P-Value, |
|
11th Week |
One- and Two- Sample Hypothesis Testing (for a Mean and Mean Differences) |
|
12th Week |
Simple Linear Regression and Correlation |
|
13th Week |
Analysis of Variance Application Lack-of-fit Test |
|
14th Week |
Introduction to Multivariate Regression Analysis. Quality engineering applications. |
|
15th Week |
|
|
| Recommended or Required Reading | Walpole R.E., Myers R.H. Myers Sh. L. Ye K. Probability and Statistics or Engineers and Scientists Prentice Hall. 7th edition.
Kara, İ., Olasılık, Bilim Teknik Yayınevi, İstanbul, 2000.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Questions/Answers
- Problem Solving
- Other
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Assignment |
4 |
10 |
| Quiz |
4 |
20 |
| Attendance |
14 |
5 |
| 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 |
2 |
2 |
| Preparation for Quiz |
4 |
4 |
16 |
| Individual or group work |
14 |
12 |
168 |
| Preparation for Final exam |
1 |
20 |
20 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
20 |
20 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2 |
2 |
| Homework |
4 |
6 |
24 |
| Total Work Load | 294 |
| Total Work Load / 30 (h) | 9.8 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
