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Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course General Introduction Information

Course Code:

DEN111

Course Name:

Computed Aided Biostatistics

Course Semester:

Fall

Course Credits:

ECTS

Language of instruction:

Course Requirement:

Does the Course Require Work Experience?:

Type of course:

Necessary

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi AYHAN PARMAKSIZ

Course Lecturer(s):

Assist. Prof Ayhan Parmaksız

Course Assistants:

Course Purpose and Content

Course Objectives:	To teach the student basic statistical concepts and methods with examples and applications specific to the field of health, to enable the student to understand and evaluate the literature in her field from a statistical perspective.
Course Content:	Basic statistical concepts, Descriptive measurements, Theoretical distributions (Normal distribution), Sample distributions, Basic research methods, Basic sampling methods, Hypothesis tests, Relationship measures, Linear regression analysis.

Learning Outcomes

The students who have succeeded in this course;
1) Decide on appropriate basic statistical analyses.
2) Performs calculations and analyzes on its own.
3) Interprets statistical test results
4) Understands the statistical analyzes in the literature in his field.
5) Critiques the statistical analyzes in the literature in his field.
6) Have sufficient theoretical and practical basis for more advanced statistics courses.

Course Flow Plan

Week	Subject	Related Preparation
1)	Basic statistical concepts; statistics, biostatistics, areas of use of biostatistics, universe, sample, statistics, parameters, data, variables, data types, etc.
1)	Basic statistical concepts; statistics, biostatistics, areas of use of biostatistics, universe, sample, statistics, parameters, data, variables, data types, etc.
2)	Descriptive statistics; Classification of data, mean and position measures
3)	Descriptive Statistics: Measures of dispersion
4)	Examination of relationships between variables with tables and graphs: Cross-tabulations, tables by descriptive measures (mean, standard deviation, etc.), multivariate applications of basic graphical representations, scatter plots, etc.
5)	Probability and Standard normal distribution
6)	Sample distributions and confidence intervals: Sample distribution of the mean and ratio, confidence intervals and interpretation.
7)	Sample distributions and confidence intervals: Sample distribution of the mean and ratio, confidence intervals, and interpretation
8)	Research methods. Introduction to hypothesis testing: Purpose of hypothesis testing, stages, errors, p and alpha values, power, effect size, decision-making process
9)	Hypothesis tests: Parametric one sample tests. Parametric independent two sample tests.
10)	Hypothesis tests: Parametric independent k samples tests
11)	Hypothesis tests: Parametric dependent two-sample tests. Parametric dependent k samples tests.
12)	Non-parametric hypothesis testing
13)	Relationship measures: Pearson correlation coefficient, Spearman correlation coefficient.
14)	Simple and multiple linear regression models

Sources

Course Notes / Textbooks:

References:

Daniel, Wayne W. Biostatistics 10th Edition, New York: John Wiley&Sons, 2020
Bland, Martin. An Introduction to Medical Statistics 4th Edition, Oxford Publication, 2020.
Alpar R. Spor, Sağlık ve Eğitim Bilimlerinden Örneklerle UYGULAMALI İSTATİSTİK ve GEÇERLİK-GÜVENİRLİK. Detay Yayıncılık, Ankara, 2018.
Sümbüloglu K ve Sümbüloğlu V. Biyoistatistik. Seçkin Yayıncılık, Ankara, 2010.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Medium	3 Highest

	Program Outcomes	Level of Contribution
1)	To have advanced theoretical and applied knowledge supported by textbooks, application tools and other resources containing up-to-date information in the field.
2)	To be able to use advanced theoretical and applied knowledge gained in the field.
3)	To be able to interpret and evaluate data, to define and analyze problems, to develop solutions based on research and evidence by using advanced knowledge and skills in the field.
4)	To be able to inform the relevant persons and institutions on the issues related to the field; to be able to convey their thoughts and suggestions for solutions to problems verbally and in writing.
5)	To be able to share with experts and non-experts, by supporting with quantitative and qualitative data, thoughts and solution suggestions for problems related to the field.
6)	Being able to organize and implement projects and activities for the social environment in which they live with the awareness of social responsibility.
7)	Being able to critically evaluate the advanced knowledge and skills acquired in the field
8)	Ability to identify learning needs and direct learning
9)	Developing a positive attitude towards lifelong learning
10)	To act in accordance with social, scientific, cultural and ethical values in the stages of collecting, interpreting, applying and announcing the results of the data related to the field.
11)	To have sufficient awareness of the universality of social rights, social justice, quality culture and protection of cultural values, environmental protection, occupational health and safety.
12)	Being able to carry out an advanced study in the field independently
13)	To be able to take responsibility individually and as a team member in order to solve unforeseen complex problems encountered in applications related to the field.

Learning Activity and Teaching Methods

Anlatım
Course
Homework

Measurement and Evaluation Methods and Criteria

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Presentation	1	% 10
Midterms	1	% 30
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Aktiviteye Hazırlık	Aktivitede Harçanan Süre	Aktivite Gereksinimi İçin Süre	Workload
Course Hours	28	3			84
Presentations / Seminar	1	50			50
Homework Assignments	4	15			60
Midterms	1	40			40
Final	1	100			100
Total Workload					334