Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| INTRODUCTION to STATISTICAL PROGRAMMING | - | Spring Semester | 2+2 | 3 | 10 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | Second Cycle (Master's Degree) |
| Course Type | Required |
| Course Coordinator | Prof.Dr. Abdulbari BENER |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | It is aimed that students will be able to use at least one programming language in biostatistics to the extent that they can write functions, thus providing the infrastructure to apply statistical analysis. |
| Course Content | This course contains; Introduction to Programming Language,Data structures and data entries in a programming language,Vector, matrix, and other mathematical statistical operations,Graphes ,Probability Distributions,Probability,Crosstabs,One Sample Test,Bivariate Tests,One-Way Variance Analysis,Regression and correlation analysis,Multivariate Variance and Covariance Analysis,Time Series Analysis ,Logistic Regression Analysis. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Draws graphs in a programming language. | 10, 14, 5, 6, 9 | E |
| Know at least one statistical programming language. | 10, 16, 6, 9 | E |
| Solve problems related to various probability distributions in a programming language. | 10, 16, 6, 9 | E |
| Applies univariate and multivariate statistical analysis in a programming language. | 12, 14, 6, 9 | E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 5: Cooperative Learning, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | E: Homework |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Programming Language | Lecture Notes |
| 2 | Data structures and data entries in a programming language | Lecture Notes |
| 3 | Vector, matrix, and other mathematical statistical operations | Lecture Notes |
| 4 | Graphes | Lecture Notes |
| 5 | Probability Distributions | Lecture Notes |
| 6 | Probability | Lecture Notes |
| 7 | Crosstabs | Lecture Notes |
| 8 | One Sample Test | Lecture Notes |
| 9 | Bivariate Tests | Lecture Notes |
| 10 | One-Way Variance Analysis | Lecture Notes |
| 11 | Regression and correlation analysis | Lecture Notes |
| 12 | Multivariate Variance and Covariance Analysis | Lecture Notes |
| 13 | Time Series Analysis | Lecture Notes |
| 14 | Logistic Regression Analysis | Lecture Notes |
| Resources |
| İstatistikte R ile programlama, 2014, Necmi Gürsakal, Dora Yayıncılık 2. A Tiny Handbook of R, Mike Allerhand, 2011, Springer-Verlag. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can use advanced theoretical and applied knowledge gained in the fields of theoretical and applied biostatistics. | X | |||||
| 2 | Can use the knowledge of basic probability and statistics theories and applications at the level of expertise. | X | |||||
| 3 | They have knowledge of all kinds of research design in the field of health | ||||||
| 4 | Can design, construct and propose solutions for research in the field of health. | ||||||
| 5 | Can identify and analyze problems in health research and produce solutions based on scientific methods | X | |||||
| 6 | Conducts scientific clinical descriptive or analytical research on priority issues related to the field. | ||||||
| 7 | Evaluate and explain the information about the field of biostatistics with a critical approach. | ||||||
| 8 | Observes and teaches social, scientific, and ethical values in the stages of data collection, recording, interpretation, and reporting related to the field of biostatistics. | ||||||
| 9 | To be familiar with the software commonly used in the fields of biostatistics and to be able to use at least one effectively | X | |||||
| 10 | Conducts studies in the field of biostatistics independently or as a team. | ||||||
| 11 | Maintains work in the field of biostatistics individually or as a team, can participate in the decision-making process, and make and finalize the necessary planning by using time effectively. | ||||||
| 12 | Ensure the continuity of her professional development by using the biostatistics field and lifelong learning principles. | ||||||
| 13 | Publishes a scientific article in a national and international journal or presents it at a scientific meeting. | ||||||
| 14 | Take part in research, projects and activities in collaboration with other disciplines in the field of health. | ||||||
| 15 | A sensitive individual, they can use their knowledge for the benefit of society and have sufficient awareness about quality management, occupational safety, and environment in all processes. | X | |||||
| 16 | Can use the knowledge and problem-solving skills synthesized in the field of biostatistics by considering ethical principles in health research. | X | |||||
| 17 | It can be found in national and international policy studies in the field of biostatistics and education. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 0 | 0 | 0 | |||
| Guided Problem Solving | 0 | 0 | 0 | |||
| Resolution of Homework Problems and Submission as a Report | 0 | 0 | 0 | |||
| Term Project | 0 | 0 | 0 | |||
| Presentation of Project / Seminar | 0 | 0 | 0 | |||
| Quiz | 0 | 0 | 0 | |||
| Midterm Exam | 0 | 0 | 0 | |||
| General Exam | 0 | 0 | 0 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 0 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(0/30) | 0 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| INTRODUCTION to STATISTICAL PROGRAMMING | - | Spring Semester | 2+2 | 3 | 10 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | Second Cycle (Master's Degree) |
| Course Type | Required |
| Course Coordinator | Prof.Dr. Abdulbari BENER |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | It is aimed that students will be able to use at least one programming language in biostatistics to the extent that they can write functions, thus providing the infrastructure to apply statistical analysis. |
| Course Content | This course contains; Introduction to Programming Language,Data structures and data entries in a programming language,Vector, matrix, and other mathematical statistical operations,Graphes ,Probability Distributions,Probability,Crosstabs,One Sample Test,Bivariate Tests,One-Way Variance Analysis,Regression and correlation analysis,Multivariate Variance and Covariance Analysis,Time Series Analysis ,Logistic Regression Analysis. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Draws graphs in a programming language. | 10, 14, 5, 6, 9 | E |
| Know at least one statistical programming language. | 10, 16, 6, 9 | E |
| Solve problems related to various probability distributions in a programming language. | 10, 16, 6, 9 | E |
| Applies univariate and multivariate statistical analysis in a programming language. | 12, 14, 6, 9 | E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 5: Cooperative Learning, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | E: Homework |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Programming Language | Lecture Notes |
| 2 | Data structures and data entries in a programming language | Lecture Notes |
| 3 | Vector, matrix, and other mathematical statistical operations | Lecture Notes |
| 4 | Graphes | Lecture Notes |
| 5 | Probability Distributions | Lecture Notes |
| 6 | Probability | Lecture Notes |
| 7 | Crosstabs | Lecture Notes |
| 8 | One Sample Test | Lecture Notes |
| 9 | Bivariate Tests | Lecture Notes |
| 10 | One-Way Variance Analysis | Lecture Notes |
| 11 | Regression and correlation analysis | Lecture Notes |
| 12 | Multivariate Variance and Covariance Analysis | Lecture Notes |
| 13 | Time Series Analysis | Lecture Notes |
| 14 | Logistic Regression Analysis | Lecture Notes |
| Resources |
| İstatistikte R ile programlama, 2014, Necmi Gürsakal, Dora Yayıncılık 2. A Tiny Handbook of R, Mike Allerhand, 2011, Springer-Verlag. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can use advanced theoretical and applied knowledge gained in the fields of theoretical and applied biostatistics. | X | |||||
| 2 | Can use the knowledge of basic probability and statistics theories and applications at the level of expertise. | X | |||||
| 3 | They have knowledge of all kinds of research design in the field of health | ||||||
| 4 | Can design, construct and propose solutions for research in the field of health. | ||||||
| 5 | Can identify and analyze problems in health research and produce solutions based on scientific methods | X | |||||
| 6 | Conducts scientific clinical descriptive or analytical research on priority issues related to the field. | ||||||
| 7 | Evaluate and explain the information about the field of biostatistics with a critical approach. | ||||||
| 8 | Observes and teaches social, scientific, and ethical values in the stages of data collection, recording, interpretation, and reporting related to the field of biostatistics. | ||||||
| 9 | To be familiar with the software commonly used in the fields of biostatistics and to be able to use at least one effectively | X | |||||
| 10 | Conducts studies in the field of biostatistics independently or as a team. | ||||||
| 11 | Maintains work in the field of biostatistics individually or as a team, can participate in the decision-making process, and make and finalize the necessary planning by using time effectively. | ||||||
| 12 | Ensure the continuity of her professional development by using the biostatistics field and lifelong learning principles. | ||||||
| 13 | Publishes a scientific article in a national and international journal or presents it at a scientific meeting. | ||||||
| 14 | Take part in research, projects and activities in collaboration with other disciplines in the field of health. | ||||||
| 15 | A sensitive individual, they can use their knowledge for the benefit of society and have sufficient awareness about quality management, occupational safety, and environment in all processes. | X | |||||
| 16 | Can use the knowledge and problem-solving skills synthesized in the field of biostatistics by considering ethical principles in health research. | X | |||||
| 17 | It can be found in national and international policy studies in the field of biostatistics and education. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |