Course Information

Course Information
Course Title Code Language Type Semester L+U Hour Credits ECTS
-- SKY649 Turkish Compulsory 3 + 0 3.0 10.0
Prerequisite Courses
Course Level Graduate
Mode of delivery Theoretical and Presentation
Course Coordinator Prof. Dr. Yalçın KARAGÖZ
Instructor(s)
Goals Purpose of this Lesson; Basic Concepts, Z Test, t Test, Analysis of Variance, Regression and Correlation Analysis, Analysis of Covariance (ANCOVA), Canonical Correlation Analysis, Reliability and Validity Analysis, Explanatory Factor Analysis and Structural Equation Modeling, Statistical Methods Specific to the Health Field, Meta Ability to Make and Interpret Analyzes Related to the Analysis
Course Content Basic Concepts, Z Test, t Test, Analysis of Variance, Regression and Correlation Analysis, Analysis of Covariance (ANCOVA), Canonical Correlation Analysis, Reliability and Validity Analysis, Explanatory Factor Analysis and Structural Equation Modeling, Statistical Methods Specific to the Health Field, Meta Analysis Topics Will Be Explained
Learning Outcomes
# Öğrenme Kazanımı
1 Student; Basic Concepts, Z Test, t Test, Analysis of Variance, Regression and Correlation Analysis, Analysis of Covariance (ANCOVA), Canonical Correlation Analysis, Reliability and Validity Analysis, Explanatory Factor Analysis and Structural Equation Modeling, Statistical Methods Specific to the Health Field, Meta Will be able to analyze and interpret analysis topics
Lesson Plan (Weekly Topics)
Week Topics/Applications Method
1. Week Basic Concepts (Variables and their types, measurement and scale levels, establishing hypotheses, null and alternative hypotheses, significance (significance) level, power of the test, selection of appropriate statistical techniques, classification of analysis techniques (classification according to the number of variables, data characteristics). classification)) Research, Interview, Practice
2. Week Z Test (Test of the difference of a population average from a certain value, test of the difference between two population averages (independent, conjugate), test of the difference of a population ratio from a certain value, test of the difference between two population ratios) Interview, Practice, Research
3. Week t Test (Test of the difference of a population average from a certain value, test of the difference between two population averages (independent, conjugate)) Research, Interview, Practice
4. Week Variance Analysis (One Way ANOVA, Two Way ANOVA) Research, Interview, Practice
5. Week Analysis of Variance (One-Way MANOVA, Two-Way MANOVA) Research, Interview, Practice
6. Week Regression and Correlation Analysis (Basic concepts in regression analysis, Estimation in Bivariate Regression Models) Interview, Practice, Research
7. Week Regression and Correlation Analysis (Multivariate Regression Analysis, Selection of Variables to be Entered into the Model, Estimation of the Function to be Used in the Model (Curve Estimation), Graph Drawing in Regression) Practice, Interview, Research
8. Week Covariance Analysis (ANCOVA), Canonical Correlation Analysis Research, Interview, Practice
9. Week Reliability and Validity Analysis Research, Practice, Interview
10. Week Exploratory Factor Analysis and Structural Equation Modeling (Basic concepts in structural equation modeling, Fit Indices) Interview, Research, Practice
11. Week Confirmatory Factor Analysis (First Level Single-Factor (Hidden Variable) Model, First Level Multi-Factor (Hidden Variable) Model, Second Level Multi-Factor (Hidden Variable) Model, Unrelated Model, Explanatory (EFA) and Confirmatory (CFA)) Comparison of Factor Analyzes) Research, Practice, Interview
12. Week Path Analysis (Path Coefficients, Path Diagram) Research, Interview, Practice
13. Week Statistical Methods Specific to the Field of Health Interview, Practice, Research
14. Week Meta Analysis Interview, Practice, Research
*Midterm and final exam dates are not specified in the 14-week course operation plan. Midterm and final exam dates are held on the dates specified in the academic calendar with the decision of the University Senate.
The Matrix for Course & Program Learning Outcomes
No Program Requirements Level of Contribution
1 2 3 4 5
3 Ability to conduct economic and financial analysis of healthcare services
6 Ability to assess and enhance health outcomes
7 Proficiency in using statistical analysis, reporting, interpretation, and decision-making
Relations with Education Attainment Program Course Competencies
Program Requirements DK1
PY3 3
PY6 3
PY7 3
Recommended Sources
Ders Kitabı veya Notu Ders Kitabı veya Ders Notu bulunmamaktadır.
Diğer Kaynaklar
  • SPSS AMOS META Applied Biostatistics (2021)., Karagöz Yalçın, Nobel Academic Publishing, Number of Editions: 3, Number of Pages 1296, ISBN: 978-625-439-583-3
  • SPSS AMOS META Applied Statistical Analysis (2019), Karagöz Yalçın, Nobel Academic Publishing, Number of editions: 3, Number of Pages 1336, ISBN: 978-605-320-547-0
  • Biostatistics (2019)., Sümbüloğlu, Kadir, Sümbüloğlu Vildan, Hatiboğlu Publishing House, Number of editions: 20, Number of pages 302, ISBN: 9789757527121
ECTS credits and course workload
ECTS credits and course workload Quantity Duration (Hour) Total Workload (Hour)
Sınavlar
Midterm 1 1 40 40
Homework 1 1 40 40
Homework 2 1 40 40
Final 1 40 40
Classroom Activities 5 19 95
Total Workload 255
*AKTS = (Total Workload) / 25,5 ECTS Credit of the Course 10.0