| Course Name | Code | Semester | T+U Hours | Credit | ECTS |
|---|---|---|---|---|---|
| Basic Analysis Techniques | YNO 506 | 0 | 3 + 0 | 3 | 6 |
| Precondition Courses | |
| Recommended Optional Courses | |
| Course Language | Turkish |
| Course Level | yuksek_lisans |
| Course Type | Compulsory |
| Course Coordinator | Doç.Dr. EMRAH ÖZSOY |
| Course Lecturers | |
| Course Assistants | Research Assistant Buket BORA |
| Course Category | |
| Course Objective | Its necessity, accurately analyzing data and interpret the results and evaluations of the examined case which is very important, scientific research stage. Addition to this, businesses are facing many problems and the solutions are waiting to be solved. Mostly, results of the analyzed data, problems can be solved. This lesson aim is to have students skills of getting the data correctly about examined case, and filterating them to be analyzed and using SPSS (Statistical Packages for the Social Sciences) with the suitable technique which is due to the aim and analyze the data and interpreting it. The student who take this lesson, have sufficiency of solving the examined phenomenon like a researcher or academician. |
| Course Content | This lesson consists of, the concept of data and identify the data, choosing statistical analyses according to the research aim and in this context, descriptive statistics, tests of comparing two and more groups non-parametric tests correlation and regression analyses, factor analyses, cluster analyses which are multivariable statistical analyses. |
| # | Course Learning Outcomes | Teaching Methods | Assessment Methods |
|---|---|---|---|
| 1 | Recognizes data properties obtained from research | Lecture, Question-Answer, | Testing, Homework, |
| 2 | An appropriate data collection tool is able to be composed in the resarch case. | Lecture, Drilland Practice, | Testing, Homework, |
| 3 | Best fit data can be prepared in the research case | Lecture, Drilland Practice, | Testing, Homework, |
| 4 | For propose and data properties, learner identifies most apropriate analysis technic for the research | Lecture, Drilland Practice, | Testing, Homework, |
| 5 | An appropriate analysis technic can be analysed for available data with SPSS | Lecture, Drilland Practice, | Testing, Homework, |
| 6 | Result of analysis can be interpreted and judged | Lecture, Drilland Practice, | Testing, Homework, |
| Week | Course Topics | Preliminary Preparation |
|---|---|---|
| 1 | The concept of data and attainmet data techniques | |
| 2 | Choosing statistical technique for data analyses | |
| 3 | Introduction to SPSS Package Programme | |
| 4 | Data processes in SPSS | |
| 5 | Data processes in SPSS | |
| 6 | Descriptive Statistis | |
| 7 | Test for comparing two groups | |
| 8 | Variace Analyses | |
| 9 | Midterm Exam | |
| 10 | Non Parametric Tests | |
| 11 | Non Parametric Tests | |
| 12 | Linear Regression and Correlation Analyses | |
| 13 | Factor Analyses | |
| 14 | Cluster Analyses |
| Resources | |
|---|---|
| Course Notes | |
| Course Resources | |
| Evaluation System | |
|---|---|
| Semester Studies | Contribution Rate |
| 1. Ödev | 100 |
| Total | 100 |
| 1. Yıl İçinin Başarıya | 40 |
| 1. Final | 60 |
| Total | 100 |
| ECTS - Workload Activity | Quantity | Time (Hours) | Total Workload (Hours) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
| Hours for off-the-classroom study (Pre-study, practice) | 16 | 2 | 32 |
| Mid-terms | 1 | 15 | 15 |
| Assignment | 1 | 40 | 40 |
| Final examination | 1 | 20 | 20 |
| Total Workload | 155 | ||
| Total Workload / 25 (Hours) | 6.2 | ||
| dersAKTSKredisi | 6 | ||