Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
9303135232003Computational Biostatistics I Elective116
Level of Course Unit
Second Cycle
Language of Instruction
Turkish
Objectives of the Course
Purpose of this course, students appreciate: the significance of statistics in research , to learn the basic understanding probability and statistics , data from studies in computer functioning, graphics, tables and numerical methods to analyze the ability of özetleyebilmesi and the course is to provide the level.
Name of Lecturer(s)
Assist. Prof. Dr. Timur KÖSE
Learning Outcomes
1Araştırmanın planlanma aşamasında, istatistiksel desteğe ihtiyaç olabileceğinin farkında olma.
2Herhangi bir verinin ölçüm skalasını anlama ve skalaya uygun grafik, tablo ve sayısal özetleme yöntemlerini bilme.
3Olayların olasılığı ile ilgili toplama ve çarpma kurallarını, bağımlılık ve bağımsızlık kavramlarını bilme ve hesaplamada kullanma.
4Kesikli şans değişkenlerine ilişkin Binom ve Poisson Dağılışlarını bilme, verilen bir probleme uygun dağılışı kullanrak çözüm üretme.
5Sürekli şans değişkenlerine ilişkin Normal Dağılışı bilme, verilen bir problemle ilgili olarak olasılıkları hesaplama.
6Basit tesadüfi, sistematik, tabakalı ve küme örneklemsi yöntemlerini bilme ve uygulama.
7Populasyon parametresi ile örnek istatistikleri arasındaki farklılıkları kavrama.
8Merkezi limit teoremini, güven aralığı ve hipotez testi ile ilgili hata ve güven kavramlarını bilme.
9Tek örnek ya da eşleştirilmiş iki örnek durumunda kullanılan Student-t Testi, Wilcoxon Testi yöntemlerini bilme ve verinin gereklerine uygun kullanma.
10Bağımsız iki örnek durumunda kullanılan Student-t Testi, ve Mann-Whitney U Testi Testi yöntemlerini bilme ve verinin gereklerine uygun kullanma.
11Kategorik verilerin analizleri ile ilgili Ki-Kare, Fisher Tam Olasılık ve Mc. Nemar Testi yöntemlerini bilme ve verinin gereklerine uygun kullanma.
12İki değişken arasındaki doğrusal ilişkiyi ölçmek amacıyla Pearson ve Spearman korelasyon analizi yöntemlerini bilme ve verinin gereklerine uygun kullanma.
13Araştırmada elde edilen verileri bilgisayar ortamında derleme ve dersin kapsamı kadarı ile analiz etme.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Lot of statistics in research. Measurement scale of variables and data summarizing techniques ppropriate to scale of data . Basic rules and concepts of probability. Discrete and continuous random variables and some basic probability distributions. Basic concepts of sampling methods, sampling distributions, estimation and hypothesis testing . One example of problems related to the dependent and independent two-sample estimation and hypothesis testing methods. Data compilation and analysis of the use of computer software in order.
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1The place and importance of statistics in research. Nominal, Ordinal and numeric scale of measurements and their properties. Data summarization methods by using tables and graphics.
2Measures of central tendency and variability.
3Computer programs
4Applications with computer
5Concepts and rules related with probability. Binomial Distribution.Solving problems about distributions
6Poisson and Normal DistributionsSolving problems about distributions
7Sampling methods and sampling distributions
8Midterm
9Confidence intervals and hypothesis testing
10Student-t and Wilcoxon Tests for one sample and paired two samples case
11Student-t and Wilcoxon Tests for one sample and paired two samples caseApplications with computer
12Student-t Test ve Mann-Whitney U Test for two independen samplesApplications with computer
13Categorical data analysis: Chi-Square, Fisher Exact and Mc. Nemar TestsApplications with computer
14Linear relationship between two variables: Pearson and Spearman correlation analysis methods Applications with computer
15Final exam
Recommended or Required Reading
İkiz F., Püskülcü H., Eren Ş., "İstatistiğe Giriş", Barış Yayınları Fakülteler Kitabevi, 2006 (7. Baskı) Dawson B., Trapp R. G., "Basic & Clinical Biostatistics", McGraw-Hill, 2004 (4. Baskı) Softwares for data management and analysis.
Planned Learning Activities and Teaching Methods
Activities are given in detail in the sections of "Assessment Methods and Criteria" and "Workload Calculation".
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
Midterm Examination1100
SUM100
End Of Term (or Year) Learning ActivitiesQuantityWeight
Final Sınavı1100
SUM100
Term (or Year) Learning Activities40
End Of Term (or Year) Learning Activities60
SUM100
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination122
Final Examination122
Attending Lectures12336
Practice616
Self Study12112
Individual Study for Homework Problems12112
Individual Study for Mid term Examination144
Individual Study for Final Examination144
Reading12112
TOTAL WORKLOAD (hours)90
Contribution of Learning Outcomes to Programme Outcomes
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* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr