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  Course Description
Course Name : Analysis of Variance

Course Code : ISB-544

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Prof.Dr. SADULLAH SAKALLIOĞLU

Learning Outcomes of the Course : Have the knowledge of the terms regarding the experimental and sampling units
Understand the basic logic of analysis of variance.
Determine how the level of the factor affects mean response
Perform parameter estimation and confidence interval
Perform hypothesis testing for analysis of variance models

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : To teach different methods used in the design of experiments and examine how these methods are connected to statistical models.

Course Contents : Principles of experimental design; Analysis of variance models; One-way analysis of variance: Balanced case; Two-way analysis of variance: Balanced case; Analysis of variance: Unbalanced case; Analysis of covariance; Random effect models and mixed effect models

Language of Instruction : Turkish

Work Place : Department Seminar Room


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Designing an experiment Reading the references Lecture, discussion
2 One-way analysis of variance with fixed effects Reading the references Lecture, discussion
3 Checking if the data fit model, parameter estimation, confidence intervals Reading the references Lecture, discussion and use the statistical package programs
4 One-way analysis of variance with random effects Reading the references Lecture, discussion
5 Checking if the data fit the model, parameter estimation, confidence intervals Reading the references Lecture, discussion and use the statistical package programs
6 Balanced two-way factorial design with fixed effects Reading the references Lecture, discussion
7 Balanced two-way factorial design with frandom effects Reading the references Lecture, discussion
8 Mid-term exam, homework Review the topics discussed in the lecture notes and sources Written exam
9 Unbalanced two-way factorial design with fixed effects Reading the references Lecture, discussion
10 Parameter estimation, confidence intervals Reading the references Lecture, discussion and use the statistical package programs
11 Randomized Complete block design Reading the references Lecture, discussion
12 Mixed models Reading the references Lecture, discussion
13 Estimation and confidence intervals for variance components Reading the references Lecture, discussion and use the statistical package programs
14 Repeated measures designs Reading the references Lecture, discussion
15 Analysis of variance table and F tests Reading the references Lecture, discussion
16/17 Final exam Review the topics discussed in the lecture notes and sources Written exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Rencher, A. C. (2000), Linear Models in Statistics, Wiley and Sons Inc., New York.
 Mickey, R.M.; Dunn, O.J.; Clark, V.A. (2004), Applied Statistics, Analysis of Variance and Regression, Wiley and Sons Inc..
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 60
    Homeworks/Projects/Others 5 40
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Possess advanced level of theoretical and applicable knowledge in the field of Probability and Statistics. 3
2 Conduct scientific research on Mathematics, Probability and Statistics. 3
3 Possess information, skills and competencies necessary to pursue a PhD degree in the field of Statistics. 4
4 Possess comprehensive information on the analysis and modeling methods used in Statistics. 5
5 Present the methods used in analysis and modeling in the field of Statistics. 4
6 Discuss the problems in the field of Statistics. 1
7 Implement innovative methods for resolving problems in the field of Statistics. 1
8 Develop analytical modeling and experimental research designs to implement solutions. 5
9 Gather data in order to complete a research. 3
10 Develop approaches for solving complex problems by taking responsibility. 3
11 Take responsibility with self-confidence. 3
12 Have the awareness of new and emerging applications in the profession 3
13 Present the results of their studies at national and international environments clearly in oral or written form. 3
14 Oversee the scientific and ethical values during data collection, analysis, interpretation and announcment of the findings. 4
15 Update his/her knowledge and skills in statistics and related fields continously 3
16 Communicate effectively in oral and written form both in Turkish and English. 3
17 Use hardware and software required for statistical applications. 4
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
    Homeworks, Projects, Others 5 6 30
    Mid-term Exams (Written, Oral, etc.) 1 8 8
    Final Exam 1 18 18
Total Workload: 140
Total Workload / 25 (h): 5.6
ECTS Credit: 6