Ä°ST651 - SEQUENTIAL ANALYSIS

Course Name Code Semester Theory
(hours/week)		 Application
(hours/week)		 Credit ECTS
SEQUENTIAL ANALYSIS Ä°ST651 2nd Semester 3 0 3 8
PrequisitesNO
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Discussion
Drill and Practice
Brain Storming
 
Instructor (s)Prof. Dr. Sevil BACANLI 
Course objective 
Learning outcomes
    Course Content 
    References1. Wald, A. Sequential Analysis, Dover Publications, New- York, 1947; Second Edition, 1973..?
    2. Govindarajulu, Z., The Sequential Statistical Analysis of Hypothesis Testing, Point and Interval Estimation and Decision Theory, American Science Press, Columbus, Ohio,1982.
    3. Jennison C. Turnbull BW (2000) Group sequential methods with applications to ciinicaJ trials. Chapman & Hall.

    4. Çıngı H.; Kadılar, C., (2005 ). Ardıs?ık Çözümleme. Bizim Büro Basımevi.
    5. Peker,Ö.K., Bacanlı, S., (2015). A Group Sequential Test of Circular Data Using the Von-Mises Distribution ,Hacettepe Journal of Mathematics and Statistic.?
    6. KaradaÄŸ,Ö.,Bacanlı,S., (2020) Hypothesis testing for the inverse Gaussian distribution mean based on ranked set sampling ,Journal of Statistical Computation and Simulation 2020, Vol. 90, No. 13, 2384?239 

    Course outline weekly

    WeeksTopics
    Week 1
    Week 2
    Week 3
    Week 4
    Week 5
    Week 6
    Week 7
    Week 8
    Week 9
    Week 10
    Week 11
    Week 12
    Week 13Article Review
    Week 14
    Week 15Article Presantation
    Week 16Final exam

    Assesment methods

    Course activitiesNumberPercentage
    Attendance00
    Laboratory00
    Application00
    Field activities00
    Specific practical training00
    Assignments215
    Presentation15
    Project00
    Seminar00
    Midterms130
    Final exam150
    Total100
    Percentage of semester activities contributing grade succes150
    Percentage of final exam contributing grade succes150
    Total100

    WORKLOAD AND ECTS CALCULATION

    Activities Number Duration (hour) Total Work Load
    Course Duration (x14) 14 3 42
    Laboratory 0 0 0
    Application5210
    Specific practical training000
    Field activities000
    Study Hours Out of Class (Preliminary work, reinforcement, ect)000
    Presentation / Seminar Preparation16060
    Project000
    Homework assignment41040
    Midterms (Study duration)13838
    Final Exam (Study duration) 15050
    Total Workload26163240

    Matrix Of The Course Learning Outcomes Versus Program Outcomes

    D.9. Key Learning OutcomesContrubition level*
    12345
    1. improves the undergraduade theoretical and applied knowlege   X 
    2. does researches with focusing on a specific area    X 
    3. offers new solutions to statistical problems    X
    4. uses the profiency knowlegde gained in Statistics in interdiscipliner studies    X
    5. presents a particular subject on Statistics in a certain time effectively    X
    6. fullfilles new projects and events on Statistics. Has the ability of conducting, carrying out and reporting a project.    X 
    7. has the ability of scientific reasoning.    X 
    8. has the ability of analythic thinking   X 
    9. follows up the new developments on proficiency in both national and international area    X
    10. follows the statistics literature.    X
    11. uses the Information technologies in advance level   X 
    12. has capable of individual study and independent decision making   X 
    13. Has the necessary qualifications for team work and team leader   X 
    14. Improves a foreign language to follow the relevant literature and to present those studies   X 
    15. has the professional and ethical responsibility    X

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest