Computer Programming
Course Details
KTO KARATAY UNIVERSITY
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 03820103 | Computerized Statistics | 1 | Spring | 2 | 3+1+0 | 7 | 7 |
| Course Type | Compulsory |
| Course Cycle | Associate (Short Cycle) (TQF-HE: Level 5 / QF-EHEA: Short Cycle / EQF-LLL: Level 5) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Lect. Özlem AKARÇAY PERVİN |
| Instructor(s) | Lect. Özlem AKARÇAY PERVİN |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Lect. Özlem AKARÇAY PERVİN | TSMYO-T213 | [email protected] | 7916 |
Course Content
Probability calculations, statistical analysis, hypothesis testing
Objectives of the Course
Bu ders ile öğrencinin temel istatistik işlemlerini öğrenmesi ve bilgisayarda istatistik yazılım programı ile uygulama yapması amaçlanmaktadır.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | X |
| Specialization / Field Courses | X |
| Support Courses | X |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P4 | Effectively uses information technologies (software, programs, animations, etc.) related to her/his profession. | 4 |
| P1 | He/she has basic, current and applied information about his/her profession. | 5 |
| P3 | He/She follows current developments and practices in his profession and uses them effectively. | 4 |
| P5 | Has the ability to independently evaluate professional problems and issues with an analytical and critical approach and propose solutions. | 3 |
| P6 | Can present his/her thoughts effectively through written and verbal communication at the level of knowledge and skills and expresses them in an understandable manner. | 5 |
| P9 | It has social, scientific, cultural and ethical values in the stages of collecting data related to its field, applying it and announcing the results. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Knows effective research and solution techniques to identify problems. | P.8.3 | 1 |
| O2 | Knows current techniques for data analysis. | P.3.1 | 1 |
| O3 | Analyzes complex problems and develops solution strategies | P.3.4 | 1 |
| O4 | Have basic analysis knowledge. | P.3.5 | 1 |
| O5 | Ability to write reports using basic statistical information | P.6.1 | 1,7 |
| O6 | Ability to conduct computer and data science analyses and report results | P.6.3 | 1 |
| O7 | Follows ethical standards in data collection and analysis | P.9.2 | 1 |
| O8 | Applies scientific research methods and evaluates the results objectively. | P.9.3 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | data collection |
| 2 | Converting data to series |
| 3 | Data entry and basic analysis with a statistical software program on the computer |
| 4 | Calculating measures of variability of series |
| 5 | Calculating probabilities |
| 6 | Probability calculations with a statistical software program on the computer |
| 7 | Analyzing with random variables |
| 8 | Hypothesis Testing |
| 9 | Learning about hypothesis testing |
| 10 | Learning about test types |
| 11 | Analyzing the relationship between variables |
| 12 | Regression analysis |
| 13 | Regression analysis |
| 14 | Correlation analysis |
Textbook or Material
| Resources | Introduction to Probability Models-Sheldon M. Ross |
| SPSS Kullanma Kılavuzu : SPSS ile Adım Adım Veri Analizi |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 5 | 70 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 5 | 70 |
| Midterms | 1 | 15 | 15 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 14 | 1 | 14 |
| Laboratory | 14 | 1 | 14 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 15 | 15 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 198 | ||
| Total Work Load / 30 | 6,60 | ||
| Course ECTS Credits: | 7 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P3 | P6 | P8 | P9 |
|---|---|---|---|---|---|
| O1 | Knows current techniques for data analysis. | 5 | - | - | - |
| O2 | Analyzes complex problems and develops solution strategies | - | - | - | - |
| O3 | Have basic analysis knowledge. | 5 | - | - | - |
| O4 | Ability to write reports using basic statistical information | - | 5 | - | - |
| O5 | Ability to conduct computer and data science analyses and report results | - | - | - | - |
| O6 | Knows effective research and solution techniques to identify problems. | - | - | - | - |
| O7 | Follows ethical standards in data collection and analysis | - | - | - | 5 |
| O8 | Applies scientific research methods and evaluates the results objectively. | - | - | - | 5 |