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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    M.SC. in Computer Engineering (Without Thesis)

    STAT 505 | Course Introduction and Application Information

    Course Name
    Applied Statistical Analysis
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    STAT 505
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator -
    Course Lecturer(s)
    Assistant(s)
    Course Objectives This course provides essential materials for analyzing statistical data appear in various fields of science such as engineering, medicine and finance
    Learning Outcomes

    The students who succeeded in this course;

    • will be able to describe descriptive information using data.
    • will be able to list and summarize statistical data.
    • will be able to identify outlier data among the data.
    • will be able to calculate estimators for statistical data.
    • will be able to put forward and test hypotheses for statistical data.
    • will be able to analyze the relationship between one or more random variables.
    • will be able to calculate statistical data and nonparametric estimators.
    Course Description This course provides essential materials for analyzing statistical data appear in various fields of science.

     



    Course Category

    		Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Why to study statistics and the concept of decision making in an uncertain environment. Importance of describing data and summarizing descriptive relationships. "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 1 (Pages: 1-17)
    2 Sampling Methods and the Central Limit Theorem, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 8 (Pages: 250-281)
    3 Estimation and Confidence Intervals, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 9 (Pages: 282-317)
    4 One-Sample Tests of Hypothesis, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 10 (Pages: 318-352)
    5 Two-Sample Tests of Hypothesis, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 353-385)
    6 Analysis of Variance, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 12 (Pages: 386-434)
    7 Midterm
    8 Correlation and Linear Regression, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 436-487)
    9 Correlation and Linear Regression, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 436-487)
    10 Multiple Regression Analysis, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 488-544)
    11 Multiple Regression Analysis, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 488-544)
    12 Nonparametric Methods: Nominal Level Hypothesis Tests, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 545-581)
    13 Nonparametric Methods: Analysis of Ordinal Data, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 582-620)
    14 Nonparametric Methods: Analysis of Ordinal Data, Applications of Excel "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition, 2017. ISBN-13: 978-1259666360 Chapter 11 (Pages: 582-620)
    15 Semester Review
    16 Final Exam

     

    Course Notes/Textbooks

    "Statistical Techniques in Business & Economics (Student edition)" by D. Lind, W. Marchal, S. Wathen, McGraw-Hill, 17th Edition,  2017. ISBN-13: 978-1259666360
    Suggested Readings/Materials

    Statistical Techniques for Data Analysis” by J.K. Taylor and C. Cihon, Chapman&Hall, 2nd Edition, 2004. ISBN-13: 978-1584883852

    “Statistical Inference” by G. Casella and R. L. Berger, Duxbury Press, 1st Edition, 1990. ISBN-13: 978-0534119584

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    Presentation / Jury
    1
    10
    Project
    1
    20
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    30
    Final Exam
    1
    40
    Total

    Weighting of Semester Activities on the Final Grade
    3
    60
    Weighting of End-of-Semester Activities on the Final Grade
    1
    40
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    14
    5
    70
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    0
    Presentation / Jury
    1
    12
    12
    Project
    1
    20
    20
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    30
    30
    Final Exam
    1
    45
    45
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    		 PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.
    -
    -
    -
    X
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    -
    X
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.
    -
    -
    -
    X
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    -
    X
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    X
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.
    -
    -
    -
    -
    X
    7 Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.
    -
    -
    -
    X
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.
    -
    -
    -
    -
    X
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    X
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    X
    -
    -
    11 Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.
    -
    -
    X
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    -
    X
    -
    -
    -

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

     

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