Orthodontics (DR) | |||||
PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 |
Course Code: | SAY613 | ||||||||
Course Name: | İleri Biyoistatistik | ||||||||
Course Semester: | Fall | ||||||||
Course Credits: |
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Language of instruction: | |||||||||
Course Requisites: | |||||||||
Does the Course Require Work Experience?: | No | ||||||||
Type of course: | Compulsory | ||||||||
Course Level: |
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Mode of Delivery: | Face to face | ||||||||
Course Coordinator : | Dr.Öğr.Üyesi DUYGU AYDIN HAKLI | ||||||||
Course Lecturer(s): |
Öğr.Gör. ŞİRİN YILMAZ Dr.Öğr.Üyesi NEVZAT BİLGİN |
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Course Assistants: |
Course Objectives: | To teach the subject how to approach within the scope of multivariate statistics, how to analyze with basic multivariate approaches and to gain knowledge and experience on how to interpret the findings. To learn how to use in scientific publications. |
Course Content: | Basic Biostatistics Concepts Introduction to Multivariate Analysis Multiple Regression Canonical Correlation Logistic Regression Analysis Covariance Analysis Multivariate Analysis |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Basic concept of statistics | |
2) | Data matrix and descriptive statistics in multivariate analysis | |
3) | Multivariate graphics. | |
4) | Standardization, multivariate normal distribution and examining the normality. | |
5) | Multivariate outliers, similarity and dissimilarity measures | |
6) | Missing value analysis. | |
7) | Multivariate hypothesis tests, multivariate test of population mean, testing homogeneity of variance-covariance matrices (Box M), Bartlett?s test of sphericity. Hotelling's T2. | |
8) | MANOVA (Multivariate one way analysis of variance). Multivariate two-way analysis of variance, variance analysis for repeated measures. | |
9) | Multiple Linear Regression Analysis. | |
10) | Article critisicm | |
11) | Explanatory factor analysis: Aim, importance and usage. Factor extraction methods, determining the number of factors, factor loadings, eigenvalues, factor scores and interpretation of factor scores. Factor rotation and factor rotation methods. Factor analysis and construct validity. | |
12) | Canonical Correlation. Aims of canonical correlation, calculating and interpreting the canonical coefficients, etc. | |
13) | Logistic regression. Aims of logistic regression, calculating and interpreting the coefficients, etc. | |
14) | Final exam- Article critisicm |
Course Notes / Textbooks: | Ders notları haftalık bazda verilecektir. Her hafta makale kritiği yapılacaktır. |
References: | 1. Andy Field, Discovering Statistics Using SPSS, SAGE Publications,2009. |
Learning Outcomes | 1 |
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3 |
4 |
5 |
6 |
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Program Outcomes | ||||||
1) To be able to diagnose, identify and classify dental and skeletal anomalies. To gain theoretical and practical knowledge about orthodontic treatment methods. To be able to perform and interpret the cephalometric analyzes and soft tissue analyzes required for diagnosis and treatment prediction on one's own. To be able to make appropriate treatment plans for the diagnosed cases. | ||||||
2) To have the knowledge and clinical experience to treat orthodontic cases with contemporary removable and fixed orthodontic treatment methods. To be able to make orthognathic surgery planning and surgical preparations for patients with severe skeletal deformity, to work in coordination with the surgeons who will perform the surgery. To be able to take part in interdisciplinary working groups that coordinate the treatment of patients with cleft lip and palate, to be equipped to respond to all orthodontic needs of these patients from infancy to adulthood. To gain knowledge and experience about differential diagnosis of temporomandibular joint pathologies and treatments for them. To be able to reach the necessary resources by scanning the literature, to plan laboratory or clinical experiments using the technical and theoretical knowledge and skills gained, to take part in a thesis or a project under the supervision of a supervisor. |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | To be able to diagnose, identify and classify dental and skeletal anomalies. To gain theoretical and practical knowledge about orthodontic treatment methods. To be able to perform and interpret the cephalometric analyzes and soft tissue analyzes required for diagnosis and treatment prediction on one's own. To be able to make appropriate treatment plans for the diagnosed cases. | 1 |
2) | To have the knowledge and clinical experience to treat orthodontic cases with contemporary removable and fixed orthodontic treatment methods. To be able to make orthognathic surgery planning and surgical preparations for patients with severe skeletal deformity, to work in coordination with the surgeons who will perform the surgery. To be able to take part in interdisciplinary working groups that coordinate the treatment of patients with cleft lip and palate, to be equipped to respond to all orthodontic needs of these patients from infancy to adulthood. To gain knowledge and experience about differential diagnosis of temporomandibular joint pathologies and treatments for them. To be able to reach the necessary resources by scanning the literature, to plan laboratory or clinical experiments using the technical and theoretical knowledge and skills gained, to take part in a thesis or a project under the supervision of a supervisor. | 1 |
Expression | |
Lesson | |
Reading | |
Q&A / Discussion | |
Application (Modelling, Design, Model, Simulation, Experiment etc.) |
Presentation |
Semester Requirements | Number of Activities | Level of Contribution |
Presentation | 2 | % 50 |
Final | 1 | % 50 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 50 | |
PERCENTAGE OF FINAL WORK | % 50 | |
total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Study Hours Out of Class | 28 | 8 | 224 |
Presentations / Seminar | 2 | 40 | 80 |
Homework Assignments | 3 | 3 | 9 |
Midterms | 1 | 50 | 50 |
Final | 1 | 50 | 50 |
Total Workload | 455 |