Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| INTRODUCTION to BIOSTATISTICS | - | Yearly | 16+4 | - | 2 |
| Course Program | Pazartesi 09:00-09:45 Pazartesi 10:00-10:45 Salı 09:00-09:45 Salı 10:00-10:45 Çarşamba 09:00-09:45 Çarşamba 10:00-10:45 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Committee Course |
| Course Coordinator | Prof.Dr. Mehmet KOÇAK |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | This course begins by an introduction of main statistical concepts, types of measurements used in statistical analysis, and sampling strategies and types of research designs, followed by examples of statistical graphics. Descriptive statistics will be defined and examples will be discussed as the first step of data analysis. Following a brief introduction to the concept of probability, we will discuss some of the probability distributions that are most commonly used in statistical analysis, testing and modelling, which includes Bernoulli, Binomial, Negative Binomial, Hypergeometric, Gaussian (Normal), Student-t, Chi-Square, and F distributions. Moving from descriptive statistics to inferential statistics through the concept of sampling distributions and central limit theorem, the concept of confidence intervals and hypothesis testing will be introduced and hands-on practice will be gained through examples. |
| Course Content | This course contains; Basic Definitions, Descriptive Statistics, and Statistical Graphics,Introduction to Probability and Bayes Rule,Common Random Variables,Central Limit Theorem and Sampling Distribution,Concept of Confidence Interval,Descriptive Statistics Computation Lab,Confidence Interval Computation Lab. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| At the end of this lecture, we expect that students acquire the meaning of basic terms in biostatistics, recognize basic statistics, and develop an understanding of the utility of statistical graphics. | 16, 6, 9 | A |
| At the end of this lecture, we expect that students distinguish different sampling methods, their advantages and disadvantages in different circumstances, develop understanding for various types of biases in research. | 10, 14, 16, 19, 20, 9 | A |
| At the end of this lecture, we expect that students develop an understanding of the theoretical and practical meaning of probability and recognize and appreciate probability laws. | 12, 16, 9 | A |
| At the end of this lecture, we expect that students recognize different random variables, build familiarity with their probabilistic characteristics. | 16, 6, 9 | A |
| At the end of this lecture, we expect that students develop a recognition of the importance and utility of the Central Limit Theorem and understand the mechanisms behind the probability distributions of sample statistics such as sample mean, sample proportion, and sample standard deviation. | 16, 9 | A |
| At the end of this lecture, we expect that students recognize the importance of the transition from descriptive statistics to inferential statistics and develop an understanding on how to measure the confidence we gain on population parameters through their predictors such as sample mean, sample proportion, and their two-population versions. | 10, 13, 16, 19, 6, 9 | A |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 20: Reverse Brainstorming Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Basic Definitions, Descriptive Statistics, and Statistical Graphics | Not needed |
| 2 | Introduction to Probability and Bayes Rule | Not needed |
| 3 | Common Random Variables | Introduction to Probability |
| 4 | Central Limit Theorem and Sampling Distribution | Normal Distribution |
| 5 | Concept of Confidence Interval | Central Limit Theorem and Sampling Distribution |
| 6 | Descriptive Statistics Computation Lab | |
| 7 | Confidence Interval Computation Lab |
| Resources |
| 1. Jay Kerns: Introduction to Probability and Statistics Using R, 1st Edition, G. Jay Kerns, ISBN: 978-0557249794 2. Rosner B. Fundamentals of biostatistics. Cengage learning; 8th Edition, ISBN: 978-1305268920 |
| Course notes, presentations |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | PQ1: Knows the morphological and functional normal and abnormal structure of human body. | ||||||
| 2 | PQ2: Knows the essential ways of determining the underlying causes of the pathologies with basic scientific approaches and the diagnoses of illnesses and disorders. | ||||||
| 3 | PQ3: Knows the reasons for illnesses, the ways of protection, and the methods of promotion and improvement of public health. | ||||||
| 4 | PQ4: Knows the methods of advancing his/her knowledge about health and its practice. | ||||||
| 5 | PQ5: Accesses, interprets and applies the advanced interdisciplinary information related to health. | ||||||
| 6 | PQ6: Performs a complete clinical examination of the human body, both morphologically and functionally and defines the problems. | ||||||
| 7 | PQ7: Interprets examination data for diagnoses, compares with clinical data, and provides solutions. | ||||||
| 8 | PQ8: Selects and applies appropriate tools for promotion and improvement of individual and public health. | ||||||
| 9 | PQ9: Plans and conducts an advanced study of health independently. | ||||||
| 10 | PQ10: Takes responsibility individually and as a team member to solve the problems encountered in the promotion and improvement of individual and public health. | ||||||
| 11 | PQ11: Takes responsibility for any intervention on the human body for the diagnosis and treatment. | ||||||
| 12 | PQ12: Determines personal learning requirements and decides and develops a positive lifelong learning attitude. | ||||||
| 13 | PQ13: Evaluates the information gained in the field of health with a critical approach. | ||||||
| 14 | PQ14: Informs the patient, the relevant people and institutions, and the public about the health problem and conveys recommendations of solutions in writing and/or verbally. | ||||||
| 15 | PQ15: Shares their recommendations on promotion and improvement of health with interdisciplinary experts by supporting with data. | ||||||
| 16 | PQ16: Uses English at least at the General Level of European Language Portfolio B1, follows resources in his/her field and communicates. | ||||||
| 17 | PQ17: Uses computer software, information, and communication technologies at least at the Advanced Level of European Computer Operating License. | ||||||
| 18 | PQ18: Acts in accordance with social, scientific, cultural and ethical values in the stages of obtaining, interpreting, applying and announcing the data related to the field of health. | ||||||
| 19 | PQ19: Develops strategy, policy and implementation plans on health issues and evaluate the results obtained the framework of quality processes. | ||||||
| 20 | PQ20: Systematically shares his/her works on promoting and improving health with quantitative and qualitative data and interdisciplinary experts. | ||||||
| 21 | PQ21: Has sufficient awareness on occupational health and safety issues. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 40 | |
| Rate of Final Exam to Success | 60 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 8 | 2 | 16 | |||
| Guided Problem Solving | 2 | 2 | 4 | |||
| Resolution of Homework Problems and Submission as a Report | 0 | 0 | 0 | |||
| Term Project | 8 | 2 | 16 | |||
| Presentation of Project / Seminar | 0 | 0 | 0 | |||
| Quiz | 0 | 0 | 0 | |||
| Midterm Exam | 1 | 8 | 8 | |||
| General Exam | 1 | 8 | 8 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 52 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(52/30) | 2 | |||||
| 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 BIOSTATISTICS | - | Yearly | 16+4 | - | 2 |
| Course Program | Pazartesi 09:00-09:45 Pazartesi 10:00-10:45 Salı 09:00-09:45 Salı 10:00-10:45 Çarşamba 09:00-09:45 Çarşamba 10:00-10:45 |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Committee Course |
| Course Coordinator | Prof.Dr. Mehmet KOÇAK |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | This course begins by an introduction of main statistical concepts, types of measurements used in statistical analysis, and sampling strategies and types of research designs, followed by examples of statistical graphics. Descriptive statistics will be defined and examples will be discussed as the first step of data analysis. Following a brief introduction to the concept of probability, we will discuss some of the probability distributions that are most commonly used in statistical analysis, testing and modelling, which includes Bernoulli, Binomial, Negative Binomial, Hypergeometric, Gaussian (Normal), Student-t, Chi-Square, and F distributions. Moving from descriptive statistics to inferential statistics through the concept of sampling distributions and central limit theorem, the concept of confidence intervals and hypothesis testing will be introduced and hands-on practice will be gained through examples. |
| Course Content | This course contains; Basic Definitions, Descriptive Statistics, and Statistical Graphics,Introduction to Probability and Bayes Rule,Common Random Variables,Central Limit Theorem and Sampling Distribution,Concept of Confidence Interval,Descriptive Statistics Computation Lab,Confidence Interval Computation Lab. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| At the end of this lecture, we expect that students acquire the meaning of basic terms in biostatistics, recognize basic statistics, and develop an understanding of the utility of statistical graphics. | 16, 6, 9 | A |
| At the end of this lecture, we expect that students distinguish different sampling methods, their advantages and disadvantages in different circumstances, develop understanding for various types of biases in research. | 10, 14, 16, 19, 20, 9 | A |
| At the end of this lecture, we expect that students develop an understanding of the theoretical and practical meaning of probability and recognize and appreciate probability laws. | 12, 16, 9 | A |
| At the end of this lecture, we expect that students recognize different random variables, build familiarity with their probabilistic characteristics. | 16, 6, 9 | A |
| At the end of this lecture, we expect that students develop a recognition of the importance and utility of the Central Limit Theorem and understand the mechanisms behind the probability distributions of sample statistics such as sample mean, sample proportion, and sample standard deviation. | 16, 9 | A |
| At the end of this lecture, we expect that students recognize the importance of the transition from descriptive statistics to inferential statistics and develop an understanding on how to measure the confidence we gain on population parameters through their predictors such as sample mean, sample proportion, and their two-population versions. | 10, 13, 16, 19, 6, 9 | A |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 20: Reverse Brainstorming Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Basic Definitions, Descriptive Statistics, and Statistical Graphics | Not needed |
| 2 | Introduction to Probability and Bayes Rule | Not needed |
| 3 | Common Random Variables | Introduction to Probability |
| 4 | Central Limit Theorem and Sampling Distribution | Normal Distribution |
| 5 | Concept of Confidence Interval | Central Limit Theorem and Sampling Distribution |
| 6 | Descriptive Statistics Computation Lab | |
| 7 | Confidence Interval Computation Lab |
| Resources |
| 1. Jay Kerns: Introduction to Probability and Statistics Using R, 1st Edition, G. Jay Kerns, ISBN: 978-0557249794 2. Rosner B. Fundamentals of biostatistics. Cengage learning; 8th Edition, ISBN: 978-1305268920 |
| Course notes, presentations |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | PQ1: Knows the morphological and functional normal and abnormal structure of human body. | ||||||
| 2 | PQ2: Knows the essential ways of determining the underlying causes of the pathologies with basic scientific approaches and the diagnoses of illnesses and disorders. | ||||||
| 3 | PQ3: Knows the reasons for illnesses, the ways of protection, and the methods of promotion and improvement of public health. | ||||||
| 4 | PQ4: Knows the methods of advancing his/her knowledge about health and its practice. | ||||||
| 5 | PQ5: Accesses, interprets and applies the advanced interdisciplinary information related to health. | ||||||
| 6 | PQ6: Performs a complete clinical examination of the human body, both morphologically and functionally and defines the problems. | ||||||
| 7 | PQ7: Interprets examination data for diagnoses, compares with clinical data, and provides solutions. | ||||||
| 8 | PQ8: Selects and applies appropriate tools for promotion and improvement of individual and public health. | ||||||
| 9 | PQ9: Plans and conducts an advanced study of health independently. | ||||||
| 10 | PQ10: Takes responsibility individually and as a team member to solve the problems encountered in the promotion and improvement of individual and public health. | ||||||
| 11 | PQ11: Takes responsibility for any intervention on the human body for the diagnosis and treatment. | ||||||
| 12 | PQ12: Determines personal learning requirements and decides and develops a positive lifelong learning attitude. | ||||||
| 13 | PQ13: Evaluates the information gained in the field of health with a critical approach. | ||||||
| 14 | PQ14: Informs the patient, the relevant people and institutions, and the public about the health problem and conveys recommendations of solutions in writing and/or verbally. | ||||||
| 15 | PQ15: Shares their recommendations on promotion and improvement of health with interdisciplinary experts by supporting with data. | ||||||
| 16 | PQ16: Uses English at least at the General Level of European Language Portfolio B1, follows resources in his/her field and communicates. | ||||||
| 17 | PQ17: Uses computer software, information, and communication technologies at least at the Advanced Level of European Computer Operating License. | ||||||
| 18 | PQ18: Acts in accordance with social, scientific, cultural and ethical values in the stages of obtaining, interpreting, applying and announcing the data related to the field of health. | ||||||
| 19 | PQ19: Develops strategy, policy and implementation plans on health issues and evaluate the results obtained the framework of quality processes. | ||||||
| 20 | PQ20: Systematically shares his/her works on promoting and improving health with quantitative and qualitative data and interdisciplinary experts. | ||||||
| 21 | PQ21: Has sufficient awareness on occupational health and safety issues. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 40 | |
| Rate of Final Exam to Success | 60 | |
| Total | 100 | |